library(ggplot2);library(ggpubr);library(gridExtra); library(plyr);
##
## 載入套件：'plyr'
## 下列物件被遮斷自 'package:ggpubr':
##
## mutate
library(psych);library(Hmisc); library(tidyr);library(AICcmodavg);
##
## 載入套件：'psych'
## 下列物件被遮斷自 'package:ggplot2':
##
## %+%, alpha
## 載入需要的套件：lattice
## 載入需要的套件：survival
## 載入需要的套件：Formula
##
## 載入套件：'Hmisc'
## 下列物件被遮斷自 'package:psych':
##
## describe
## 下列物件被遮斷自 'package:plyr':
##
## is.discrete, summarize
## 下列物件被遮斷自 'package:base':
##
## format.pval, units
library(car); library(Rmisc);library(lmerTest); library(emmeans); require(MuMIn)
## 載入需要的套件：carData
##
## 載入套件：'car'
## 下列物件被遮斷自 'package:psych':
##
## logit
## 載入需要的套件：lme4
## 載入需要的套件：Matrix
##
## 載入套件：'Matrix'
## 下列物件被遮斷自 'package:tidyr':
##
## expand, pack, unpack
##
## 載入套件：'lme4'
## 下列物件被遮斷自 'package:AICcmodavg':
##
## checkConv
##
## 載入套件：'lmerTest'
## 下列物件被遮斷自 'package:lme4':
##
## lmer
## 下列物件被遮斷自 'package:stats':
##
## step
## 載入需要的套件：MuMIn
##
## 載入套件：'MuMIn'
## 下列物件被遮斷自 'package:AICcmodavg':
##
## AICc, DIC, importance
rm(list = ls())
# load data and generate arrays for further analyses
load("data.Rda")
agreeableness <- c("FB02_01","FB02_02","FB02_03","FB02_04","FB02_05","FB02_06","FB02_39","FB02_40", "FB02_07","FB02_08", "FB02_09","FB02_10","FB02_11","FB02_12","FB02_13","FB02_14", "FB02_15","FB02_16","FB02_17","FB02_18","FB02_19","FB02_20","FB02_21","FB02_22", "FB02_23","FB02_24","FB02_25","FB02_26","FB02_27","FB02_28","FB02_29","FB02_30", "FB02_31","FB02_32","FB02_33","FB02_34","FB02_35","FB02_36","FB02_37","FB02_38","FB02_41","FB02_42","FB02_43","FB02_44","FB02_45","FB02_46","FB02_47","FB02_48")
trust <- c("FB02_01","FB02_02","FB02_03","FB02_04","FB02_05","FB02_06","FB02_39","FB02_40")
morality <- c("FB02_07","FB02_08", "FB02_09","FB02_10","FB02_11","FB02_12","FB02_13","FB02_14")
altruism <- c("FB02_15","FB02_16","FB02_17","FB02_18","FB02_19","FB02_20","FB02_21","FB02_22")
cooperation <- c("FB02_23","FB02_24","FB02_25","FB02_26","FB02_27","FB02_28","FB02_29","FB02_30")
modesty <- c("FB02_31","FB02_32","FB02_33","FB02_34","FB02_35","FB02_36","FB02_37","FB02_38")
sympathy <- c("FB02_41","FB02_42","FB02_43","FB02_44","FB02_45","FB02_46","FB02_47","FB02_48")
df$trust=rowMeans(df[,trust])
df$morality=rowMeans(df[,morality])
df$altruism=rowMeans(df[,altruism])
df$cooperation=rowMeans(df[,cooperation])
df$modesty=rowMeans(df[,modesty])
df$sympathy=rowMeans(df[,sympathy])
df$agreeableness = rowMeans(df[,agreeableness])
# att = attractive, matt = moderately attractive, uatt = unattractive
DG_female_att = c("DG02_01","DG03_01","DG04_01")
DG_male_att = c("DG05_01","DG06_01","DG07_01")
DG_female_matt = c("DG08_01","DG09_01","DG10_01")
DG_male_matt = c("DG11_01","DG12_01","DG13_01")
DG_female_uatt = c("DG14_01","DG15_01","DG16_01")
DG_male_uatt = c("DG17_01","DG18_01","DG19_01")
DG_all = c("DG02_01","DG03_01","DG04_01","DG05_01","DG06_01","DG07_01","DG08_01","DG09_01","DG10_01","DG11_01","DG12_01","DG13_01","DG14_01","DG15_01","DG16_01","DG17_01","DG18_01","DG19_01")
TG_female_att = c("TG02_01","TG03_01","TG04_01")
TG_male_att = c("TG05_01","TG06_01","TG07_01")
TG_female_matt = c("TG08_01","TG09_01","TG10_01")
TG_male_matt = c("TG11_01","TG12_01","TG13_01")
TG_female_uatt = c("TG14_01","TG15_01","TG16_01")
TG_male_uatt = c("TG17_01","TG18_01","TG19_01")
TG_all = c("TG02_01","TG03_01","TG04_01","TG05_01","TG06_01","TG07_01","TG08_01","TG09_01","TG10_01","TG11_01","TG12_01","TG13_01","TG14_01","TG15_01","TG16_01","TG17_01","TG18_01","TG19_01")
PD_female_att = c("PD02","PD03","PD04")
PD_male_att = c("PD05","PD06","PD07")
PD_female_matt = c("PD08","PD09","PD10")
PD_male_matt = c("PD11","PD12","PD13")
PD_female_uatt = c("PD14","PD15","PD16")
PD_male_uatt = c("PD17","PD18","PD19")
PD_all = c("PD02","PD03","PD04","PD05","PD06","PD07","PD08","PD09","PD10","PD11","PD12","PD13","PD14","PD15","PD16","PD17","PD18","PD19")
UG_female_1_att = c("UG02","UG05","UG08")
UG_male_1_att = c("UG11","UG14","UG17")
UG_female_1_matt = c("UG19","UG22","UG25")
UG_male_1_matt = c("UG28","UG31","UG34")
UG_female_1_uatt = c("UG37","UG40","UG43")
UG_male_1_uatt = c("UG46","UG49","UG52")
UG_female_3_att = c("UG03","UG06","UG09")
UG_male_3_att = c("UG12","UG15","UG55")
UG_female_3_matt = c("UG20","UG23","UG26")
UG_male_3_matt = c("UG29","UG32","UG35")
UG_female_3_uatt = c("UG38","UG41","UG44")
UG_male_3_uatt = c("UG47","UG50","UG53")
UG_female_5_att = c("UG04","UG07","UG10")
UG_male_5_att = c("UG13","UG16","UG18")
UG_female_5_matt = c("UG21","UG24","UG27")
UG_male_5_matt = c("UG30","UG33","UG36")
UG_female_5_uatt = c("UG39","UG42","UG45")
UG_male_5_uatt = c("UG48","UG51","UG54")
UG_all = c("UG02","UG05","UG08","UG11","UG14","UG17","UG19","UG22","UG25","UG28","UG31","UG34","UG37","UG40","UG43","UG46","UG49","UG52","UG03","UG06","UG09","UG12","UG15","UG55","UG20","UG23","UG26","UG29","UG32","UG35","UG38","UG41","UG44","UG47","UG50","UG53","UG04","UG07","UG10","UG13","UG16","UG18","UG21","UG24","UG27","UG30","UG33","UG36","UG39","UG42","UG45","UG48","UG51","UG54")
# Descriptive Statistics
table(df$Sex)
##
## female male divers
## 109 101 0
table(df$sexual_orientation)
##
## heterosexual homosexual bisexual
## 185 14 10
## [NA] nicht beantwortet
## 0
describe(df$Age)
## df$Age
## n missing distinct Info Mean Gmd .05 .10
## 210 0 14 0.981 21.51 3.291 18 18
## .25 .50 .75 .90 .95
## 19 21 23 25 25
##
## lowest : 18 19 20 21 22, highest: 27 32 35 40 58
##
## Value 18 19 20 21 22 23 24 25 26 27 32
## Frequency 23 43 31 27 28 13 13 23 3 2 1
## Proportion 0.110 0.205 0.148 0.129 0.133 0.062 0.062 0.110 0.014 0.010 0.005
##
## Value 35 40 58
## Frequency 1 1 1
## Proportion 0.005 0.005 0.005
# average game outcomes
df$DG_mean=rowMeans(df[,DG_all])
df$TG_mean=rowMeans(df[,TG_all])
df$PD_mean=rowMeans(df[,PD_all])
df$UG_mean=rowMeans(df[,UG_all])
# traits
des <- c("agreeableness", "trust","morality", "altruism", "cooperation", "modesty", "sympathy", "DG_mean", "TG_mean", "UG_mean","PD_mean")
des <- df[des]
describe(des)
## des
##
## 11 Variables 210 Observations
## --------------------------------------------------------------------------------
## agreeableness
## n missing distinct Info Mean Gmd .05 .10
## 210 0 82 1 3.567 0.4995 2.801 2.956
## .25 .50 .75 .90 .95
## 3.255 3.604 3.896 4.085 4.220
##
## lowest : 2.187500 2.541667 2.604167 2.645833 2.687500
## highest: 4.312500 4.395833 4.416667 4.437500 4.541667
## --------------------------------------------------------------------------------
## trust
## n missing distinct Info Mean Gmd .05 .10
## 210 0 25 0.996 3.53 0.7123 2.500 2.625
## .25 .50 .75 .90 .95
## 3.125 3.625 4.000 4.262 4.500
##
## lowest : 1.500 1.750 1.875 2.125 2.375, highest: 4.375 4.500 4.625 4.750 4.875
## --------------------------------------------------------------------------------
## morality
## n missing distinct Info Mean Gmd .05 .10
## 210 0 25 0.995 3.732 0.7441 2.500 2.750
## .25 .50 .75 .90 .95
## 3.375 3.750 4.219 4.500 4.750
##
## lowest : 1.875 2.125 2.250 2.375 2.500, highest: 4.500 4.625 4.750 4.875 5.000
## --------------------------------------------------------------------------------
## altruism
## n missing distinct Info Mean Gmd .05 .10
## 210 0 23 0.996 3.842 0.7234 2.806 3.000
## .25 .50 .75 .90 .95
## 3.375 3.875 4.375 4.625 4.750
##
## lowest : 2.125 2.375 2.500 2.625 2.750, highest: 4.500 4.625 4.750 4.875 5.000
## --------------------------------------------------------------------------------
## cooperation
## n missing distinct Info Mean Gmd .05 .10
## 210 0 24 0.994 3.481 0.6568 2.375 2.738
## .25 .50 .75 .90 .95
## 3.125 3.500 3.875 4.125 4.319
##
## lowest : 1.500 1.875 2.125 2.250 2.375, highest: 4.250 4.375 4.500 4.625 4.750
## --------------------------------------------------------------------------------
## modesty
## n missing distinct Info Mean Gmd .05 .10
## 210 0 25 0.996 3.242 0.7136 2.250 2.375
## .25 .50 .75 .90 .95
## 2.781 3.250 3.750 4.000 4.194
##
## lowest : 1.500 1.875 2.000 2.125 2.250, highest: 4.250 4.375 4.500 4.625 4.875
## --------------------------------------------------------------------------------
## sympathy
## n missing distinct Info Mean Gmd .05 .10
## 210 0 24 0.996 3.577 0.7202 2.625 2.750
## .25 .50 .75 .90 .95
## 3.125 3.625 4.125 4.375 4.500
##
## lowest : 1.750 1.875 2.125 2.250 2.500, highest: 4.375 4.500 4.625 4.750 5.000
## --------------------------------------------------------------------------------
## DG_mean
## n missing distinct Info Mean Gmd .05 .10
## 210 0 79 0.986 4.993 1.799 1.747 2.444
## .25 .50 .75 .90 .95
## 4.000 5.278 6.000 6.167 6.622
##
## lowest : 1.000000 1.277778 1.388889 1.555556 1.722222
## highest: 7.500000 8.000000 8.166667 9.000000 11.000000
## --------------------------------------------------------------------------------
## TG_mean
## n missing distinct Info Mean Gmd .05 .10
## 210 0 94 0.999 5.638 2.402 2.581 3.000
## .25 .50 .75 .90 .95
## 4.167 5.528 6.431 8.722 11.000
##
## lowest : 1.222222 1.333333 1.722222 2.000000 2.055556
## highest: 9.000000 9.166667 10.000000 10.944444 11.000000
## --------------------------------------------------------------------------------
## UG_mean
## n missing distinct Info Mean Gmd .05 .10
## 210 0 43 0.988 0.6192 0.2981 0.2778 0.3148
## .25 .50 .75 .90 .95
## 0.3519 0.6389 0.8426 1.0000 1.0000
##
## lowest : 0.00000000 0.03703704 0.07407407 0.18518519 0.22222222
## highest: 0.88888889 0.90740741 0.96296296 0.98148148 1.00000000
## --------------------------------------------------------------------------------
## PD_mean
## n missing distinct Info Mean Gmd .05 .10
## 210 0 17 0.977 0.6521 0.2971 0.2222 0.3333
## .25 .50 .75 .90 .95
## 0.5000 0.6111 1.0000 1.0000 1.0000
##
## lowest : 0.00000000 0.05555556 0.16666667 0.22222222 0.33333333
## highest: 0.77777778 0.83333333 0.88888889 0.94444444 1.00000000
##
## 0 (6, 0.029), 0.0555555555555556 (1, 0.005), 0.166666666666667 (2, 0.010),
## 0.222222222222222 (8, 0.038), 0.333333333333333 (9, 0.043), 0.388888888888889
## (8, 0.038), 0.444444444444444 (13, 0.062), 0.5 (18, 0.086), 0.555555555555556
## (24, 0.114), 0.611111111111111 (23, 0.110), 0.666666666666667 (17, 0.081),
## 0.722222222222222 (13, 0.062), 0.777777777777778 (6, 0.029), 0.833333333333333
## (3, 0.014), 0.888888888888889 (3, 0.014), 0.944444444444444 (1, 0.005), 1 (55,
## 0.262)
## --------------------------------------------------------------------------------
# correlation matrix
cor <- rcorr(as.matrix(des), type="pearson")
cor$r
## agreeableness trust morality altruism cooperation
## agreeableness 1.0000000 0.57535315 0.7700770 0.7755454 0.69850892
## trust 0.5753532 1.00000000 0.3316141 0.4582997 0.22411937
## morality 0.7700770 0.33161413 1.0000000 0.5334168 0.50776134
## altruism 0.7755454 0.45829967 0.5334168 1.0000000 0.35302232
## cooperation 0.6985089 0.22411937 0.5077613 0.3530223 1.00000000
## modesty 0.5598430 -0.03179144 0.3696399 0.1935369 0.45379492
## sympathy 0.8003944 0.41283566 0.4534612 0.6905903 0.41854524
## DG_mean 0.3112521 0.24205881 0.1757082 0.3100685 0.13186743
## TG_mean 0.1861954 0.20887960 0.1034625 0.1644796 0.06478881
## UG_mean 0.1693284 0.17923206 0.1070444 0.1342103 0.08599702
## PD_mean 0.2476996 0.20008946 0.1667274 0.1815330 0.12982703
## modesty sympathy DG_mean TG_mean UG_mean PD_mean
## agreeableness 0.55984296 0.8003944 0.3112521 0.18619535 0.16932840 0.2476996
## trust -0.03179144 0.4128357 0.2420588 0.20887960 0.17923206 0.2000895
## morality 0.36963988 0.4534612 0.1757082 0.10346245 0.10704442 0.1667274
## altruism 0.19353687 0.6905903 0.3100685 0.16447964 0.13421027 0.1815330
## cooperation 0.45379492 0.4185452 0.1318674 0.06478881 0.08599702 0.1298270
## modesty 1.00000000 0.3681262 0.1023398 0.03630575 0.06637256 0.1051956
## sympathy 0.36812620 1.0000000 0.3355494 0.19727392 0.13357068 0.2499879
## DG_mean 0.10233981 0.3355494 1.0000000 0.52113962 0.18481805 0.5001008
## TG_mean 0.03630575 0.1972739 0.5211396 1.00000000 0.31678219 0.4657020
## UG_mean 0.06637256 0.1335707 0.1848181 0.31678219 1.00000000 0.3610212
## PD_mean 0.10519558 0.2499879 0.5001008 0.46570196 0.36102123 1.0000000
cor$P
## agreeableness trust morality altruism cooperation
## agreeableness NA 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## trust 0.000000e+00 NA 8.801585e-07 2.659428e-12 1.075049e-03
## morality 0.000000e+00 8.801585e-07 NA 0.000000e+00 3.552714e-15
## altruism 0.000000e+00 2.659428e-12 0.000000e+00 NA 1.476736e-07
## cooperation 0.000000e+00 1.075049e-03 3.552714e-15 1.476736e-07 NA
## modesty 0.000000e+00 6.469037e-01 3.362688e-08 4.884772e-03 4.604761e-12
## sympathy 0.000000e+00 4.759935e-10 4.794387e-12 0.000000e+00 2.586689e-10
## DG_mean 4.259825e-06 4.007138e-04 1.074351e-02 4.652389e-06 5.640745e-02
## TG_mean 6.813495e-03 2.346074e-03 1.350770e-01 1.705222e-02 3.501713e-01
## UG_mean 1.401325e-02 9.243121e-03 1.220059e-01 5.212763e-02 2.145772e-01
## PD_mean 2.892595e-04 3.593891e-03 1.557855e-02 8.366582e-03 6.036759e-02
## modesty sympathy DG_mean TG_mean UG_mean
## agreeableness 0.000000e+00 0.000000e+00 4.259825e-06 6.813495e-03 1.401325e-02
## trust 6.469037e-01 4.759935e-10 4.007138e-04 2.346074e-03 9.243121e-03
## morality 3.362688e-08 4.794387e-12 1.074351e-02 1.350770e-01 1.220059e-01
## altruism 4.884772e-03 0.000000e+00 4.652389e-06 1.705222e-02 5.212763e-02
## cooperation 4.604761e-12 2.586689e-10 5.640745e-02 3.501713e-01 2.145772e-01
## modesty NA 3.861388e-08 1.393873e-01 6.008681e-01 3.384942e-01
## sympathy 3.861388e-08 NA 6.402950e-07 4.105172e-03 5.326834e-02
## DG_mean 1.393873e-01 6.402950e-07 NA 4.440892e-16 7.243083e-03
## TG_mean 6.008681e-01 4.105172e-03 4.440892e-16 NA 2.807572e-06
## UG_mean 3.384942e-01 5.326834e-02 7.243083e-03 2.807572e-06 NA
## PD_mean 1.286243e-01 2.528861e-04 1.088019e-14 1.060041e-12 7.320469e-08
## PD_mean
## agreeableness 2.892595e-04
## trust 3.593891e-03
## morality 1.557855e-02
## altruism 8.366582e-03
## cooperation 6.036759e-02
## modesty 1.286243e-01
## sympathy 2.528861e-04
## DG_mean 1.088019e-14
## TG_mean 1.060041e-12
## UG_mean 7.320469e-08
## PD_mean NA
# Reliabilites of the BIG 5 factor agreeableness and its facets
realiabilities_traits<- data.frame(trait=c("agreeableness", "trust", "altruism","modesty", "cooperation", "morality", "sympathy"),
alpha =c(psych::alpha(df[,agreeableness])$total$std.alpha, psych::alpha(df[,trust])$total$std.alpha,
psych::alpha(df[,altruism])$total$std.alpha, psych::alpha(df[,modesty])$total$std.alpha,
psych::alpha(df[,cooperation])$total$std.alpha, psych::alpha(df[,morality])$total$std.alpha,
psych::alpha(df[,sympathy])$total$std.alpha))
## Warning in psych::alpha(df[, agreeableness]): Some items were negatively correlated with the total scale and probably
## should be reversed.
## To do this, run the function again with the 'check.keys=TRUE' option
## Some items ( FB02_35 ) were negatively correlated with the total scale and
## probably should be reversed.
## To do this, run the function again with the 'check.keys=TRUE' option
# Reliabilities of the different faces (see Table 2 in the manuscript)
realiabilities_faces<- data.frame(sex=c("female", "male"),
DG_att =c(psych::alpha(df[,DG_female_att])$total$std.alpha, psych::alpha(df[,DG_male_att])$total$std.alpha),
DG_matt = c(psych::alpha(df[,DG_female_matt])$total$std.alpha, psych::alpha(df[,DG_male_matt])$total$std.alpha),
DG_uatt = c(psych::alpha(df[,DG_female_uatt])$total$std.alpha, psych::alpha(df[,DG_male_uatt])$total$std.alpha),
TG_att =c(psych::alpha(df[,TG_female_att])$total$std.alpha, psych::alpha(df[,TG_male_att])$total$std.alpha),
TG_matt = c(psych::alpha(df[,TG_female_matt])$total$std.alpha, psych::alpha(df[,TG_male_matt])$total$std.alpha),
TG_uatt = c(psych::alpha(df[,TG_female_uatt])$total$std.alpha, psych::alpha(df[,TG_male_uatt])$total$std.alpha),
PD_att =c(psych::alpha(df[,PD_female_att])$total$std.alpha, psych::alpha(df[,PD_male_att])$total$std.alpha),
PD_matt = c(psych::alpha(df[,PD_female_matt])$total$std.alpha, psych::alpha(df[,PD_male_matt])$total$std.alpha),
PD_uatt = c(psych::alpha(df[,PD_female_uatt])$total$std.alpha, psych::alpha(df[,PD_male_uatt])$total$std.alpha),
UG_1_att =c(psych::alpha(df[,UG_female_1_att])$total$std.alpha, psych::alpha(df[,UG_male_1_att])$total$std.alpha),
UG_1_matt = c(psych::alpha(df[,UG_female_1_matt])$total$std.alpha, psych::alpha(df[,UG_male_1_matt])$total$std.alpha),
UG_1_uatt = c(psych::alpha(df[,UG_female_1_uatt])$total$std.alpha, psych::alpha(df[,UG_male_1_uatt])$total$std.alpha),
UG_3_att =c(psych::alpha(df[,UG_female_3_att])$total$std.alpha, psych::alpha(df[,UG_male_3_att])$total$std.alpha),
UG_3_matt = c(psych::alpha(df[,UG_female_3_matt])$total$std.alpha, psych::alpha(df[,UG_male_3_matt])$total$std.alpha),
UG_3_uatt = c(psych::alpha(df[,UG_female_3_uatt])$total$std.alpha, psych::alpha(df[,UG_male_3_uatt])$total$std.alpha),
UG_5_att =c(psych::alpha(df[,UG_female_5_att])$total$std.alpha, psych::alpha(df[,UG_male_5_att])$total$std.alpha),
UG_5_matt = c(psych::alpha(df[,UG_female_5_matt])$total$std.alpha, psych::alpha(df[,UG_male_5_matt])$total$std.alpha),
UG_5_uatt = c(psych::alpha(df[,UG_female_5_uatt])$total$std.alpha, psych::alpha(df[,UG_male_5_uatt])$total$std.alpha))
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
## Number of categories should be increased in order to count frequencies.
# Manipulation Check
load("MC.Rda")
MClong$Part.Attractiveness = relevel(as.factor(MClong$Part.Attractiveness), "Matt")
MClong$Sex = relevel(as.factor(MClong$Sex), "male")
MClong$Part.Sex = relevel(as.factor(MClong$Part.Sex), "male")
model<- lmerTest::lmer(Rating ~ Sex *Part.Sex * Part.Attractiveness+(1|ID),data = MClong, REML = F)
summary(model)
## Linear mixed model fit by maximum likelihood . t-tests use Satterthwaite's
## method [lmerModLmerTest]
## Formula: Rating ~ Sex * Part.Sex * Part.Attractiveness + (1 | ID)
## Data: MClong
##
## AIC BIC logLik deviance df.resid
## 3221.8 3293.7 -1596.9 3193.8 1246
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5051 -0.5650 -0.0096 0.6070 3.3356
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 0.3364 0.5800
## Residual 0.5745 0.7579
## Number of obs: 1260, groups: ID, 210
##
## Fixed effects:
## Estimate Std. Error
## (Intercept) 3.36634 0.09497
## Sexfemale 0.02816 0.13182
## Part.Sexfemale 0.35314 0.10666
## Part.AttractivenessAtt 1.25743 0.10666
## Part.AttractivenessUatt -0.95380 0.10666
## Sexfemale:Part.Sexfemale 0.19427 0.14804
## Sexfemale:Part.AttractivenessAtt 0.62025 0.14804
## Sexfemale:Part.AttractivenessUatt -0.30309 0.14804
## Part.Sexfemale:Part.AttractivenessAtt 0.19802 0.15084
## Part.Sexfemale:Part.AttractivenessUatt -0.77558 0.15084
## Sexfemale:Part.Sexfemale:Part.AttractivenessAtt -0.73930 0.20936
## Sexfemale:Part.Sexfemale:Part.AttractivenessUatt 0.19760 0.20936
## df t value Pr(>|t|)
## (Intercept) 749.06945 35.447 < 2e-16
## Sexfemale 749.06945 0.214 0.830902
## Part.Sexfemale 1050.00000 3.311 0.000961
## Part.AttractivenessAtt 1050.00000 11.789 < 2e-16
## Part.AttractivenessUatt 1050.00000 -8.943 < 2e-16
## Sexfemale:Part.Sexfemale 1050.00000 1.312 0.189728
## Sexfemale:Part.AttractivenessAtt 1050.00000 4.190 3.03e-05
## Sexfemale:Part.AttractivenessUatt 1050.00000 -2.047 0.040878
## Part.Sexfemale:Part.AttractivenessAtt 1050.00000 1.313 0.189530
## Part.Sexfemale:Part.AttractivenessUatt 1050.00000 -5.142 3.24e-07
## Sexfemale:Part.Sexfemale:Part.AttractivenessAtt 1050.00000 -3.531 0.000432
## Sexfemale:Part.Sexfemale:Part.AttractivenessUatt 1050.00000 0.944 0.345491
##
## (Intercept) ***
## Sexfemale
## Part.Sexfemale ***
## Part.AttractivenessAtt ***
## Part.AttractivenessUatt ***
## Sexfemale:Part.Sexfemale
## Sexfemale:Part.AttractivenessAtt ***
## Sexfemale:Part.AttractivenessUatt *
## Part.Sexfemale:Part.AttractivenessAtt
## Part.Sexfemale:Part.AttractivenessUatt ***
## Sexfemale:Part.Sexfemale:Part.AttractivenessAtt ***
## Sexfemale:Part.Sexfemale:Part.AttractivenessUatt
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Sexfml Prt.Sx Prt.AA Prt.AU Sx:P.S S:P.AA S:P.AU P.S:P.AA
## Sexfemale -0.720
## Part.Sexfml -0.562 0.405
## Prt.AttrctA -0.562 0.405 0.500
## Prt.AttrctU -0.562 0.405 0.500 0.500
## Sxfml:Prt.S 0.405 -0.562 -0.720 -0.360 -0.360
## Sxfml:Pr.AA 0.405 -0.562 -0.360 -0.720 -0.360 0.500
## Sxfml:Pr.AU 0.405 -0.562 -0.360 -0.360 -0.720 0.500 0.500
## Prt.Sx:P.AA 0.397 -0.286 -0.707 -0.707 -0.354 0.509 0.509 0.255
## Prt.Sx:P.AU 0.397 -0.286 -0.707 -0.354 -0.707 0.509 0.255 0.509 0.500
## Sx:P.S:P.AA -0.286 0.397 0.509 0.509 0.255 -0.707 -0.707 -0.354 -0.720
## Sx:P.S:P.AU -0.286 0.397 0.509 0.255 0.509 -0.707 -0.354 -0.707 -0.360
## P.S:P.AU S:P.S:P.AA
## Sexfemale
## Part.Sexfml
## Prt.AttrctA
## Prt.AttrctU
## Sxfml:Prt.S
## Sxfml:Pr.AA
## Sxfml:Pr.AU
## Prt.Sx:P.AA
## Prt.Sx:P.AU
## Sx:P.S:P.AA -0.360
## Sx:P.S:P.AU -0.720 0.500
car::Anova(model, type = 3)
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: Rating
## Chisq Df Pr(>Chisq)
## (Intercept) 1256.4910 1 < 2.2e-16 ***
## Sex 0.0456 1 0.8308443
## Part.Sex 10.9624 1 0.0009298 ***
## Part.Attractiveness 432.5232 2 < 2.2e-16 ***
## Sex:Part.Sex 1.7220 1 0.1894417
## Sex:Part.Attractiveness 40.4300 2 1.662e-09 ***
## Part.Sex:Part.Attractiveness 46.5505 2 7.793e-11 ***
## Sex:Part.Sex:Part.Attractiveness 22.2573 2 1.469e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
r.squaredGLMM(model)
## Warning: 'r.squaredGLMM' now calculates a revised statistic. See the help page.
## R2m R2c
## [1,] 0.6201266 0.7604318
#Part.Attractiveness
emms <- emmeans(model, ~ Part.Attractiveness)
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness_pairwise estimate SE df t.ratio p.value
## Matt - Att -1.48 0.0526 1060 -28.174 <.0001
## Matt - Uatt 1.44 0.0526 1060 27.452 <.0001
## Att - Uatt 2.93 0.0526 1060 55.626 <.0001
##
## Results are averaged over the levels of: Sex, Part.Sex
## Degrees-of-freedom method: kenward-roger
## P value adjustment: bonferroni method for 3 tests
#Part.Sex*Part.Attractiveness
emms <- emmeans(model, ~ Part.Sex|Part.Attractiveness)
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness = Matt:
## Part.Sex_pairwise estimate SE df t.ratio p.value
## male - female -0.450 0.0744 1060 -6.054 <.0001
##
## Part.Attractiveness = Att:
## Part.Sex_pairwise estimate SE df t.ratio p.value
## male - female -0.279 0.0744 1060 -3.746 0.0002
##
## Part.Attractiveness = Uatt:
## Part.Sex_pairwise estimate SE df t.ratio p.value
## male - female 0.227 0.0744 1060 3.045 0.0024
##
## Results are averaged over the levels of: Sex
## Degrees-of-freedom method: kenward-roger
#Participant Sex*Part.Attractiveness
emms <- emmeans(model, ~ Sex|Part.Attractiveness)
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness = Matt:
## Sex_pairwise estimate SE df t.ratio p.value
## male - female -0.125 0.11 425 -1.143 0.2536
##
## Part.Attractiveness = Att:
## Sex_pairwise estimate SE df t.ratio p.value
## male - female -0.376 0.11 425 -3.430 0.0007
##
## Part.Attractiveness = Uatt:
## Sex_pairwise estimate SE df t.ratio p.value
## male - female 0.079 0.11 425 0.721 0.4714
##
## Results are averaged over the levels of: Part.Sex
## Degrees-of-freedom method: kenward-roger
#Part.Sex*Participant Sex*Part.Attractiveness
emms <- emmeans(model, ~ Part.Sex|Sex|Part.Attractiveness)
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Sex = male, Part.Attractiveness = Matt:
## Part.Sex_pairwise estimate SE df t.ratio p.value
## male - female -0.35314 0.107 1060 -3.295 0.0010
##
## Sex = female, Part.Attractiveness = Matt:
## Part.Sex_pairwise estimate SE df t.ratio p.value
## male - female -0.54740 0.103 1060 -5.306 <.0001
##
## Sex = male, Part.Attractiveness = Att:
## Part.Sex_pairwise estimate SE df t.ratio p.value
## male - female -0.55116 0.107 1060 -5.143 <.0001
##
## Sex = female, Part.Attractiveness = Att:
## Part.Sex_pairwise estimate SE df t.ratio p.value
## male - female -0.00612 0.103 1060 -0.059 0.9527
##
## Sex = male, Part.Attractiveness = Uatt:
## Part.Sex_pairwise estimate SE df t.ratio p.value
## male - female 0.42244 0.107 1060 3.942 0.0001
##
## Sex = female, Part.Attractiveness = Uatt:
## Part.Sex_pairwise estimate SE df t.ratio p.value
## male - female 0.03058 0.103 1060 0.296 0.7670
##
## Degrees-of-freedom method: kenward-roger
# Dictator Game
load("DG.Rda")
DG_long$Sex <- relevel(DG_long$Sex, ref = "male")
DG_long$Part.Sex <- relevel(DG_long$Part.Sex, ref = "male")
DG_long$ID <- as.factor(DG_long$ID)
## Models
#baseline model
ModelDG_int<- lmerTest::lmer(DG_Dec~1+(1|ID),data = DG_long, REML = F)
#confirmatory
ModelDG_agree<- lmerTest::lmer(DG_Dec~1+Sex*Part.Attractiveness*Part.Sex*agreeablenessC+(1|ID),data = DG_long,REML = F)
#without homosexual individuals
ModelDG_agree_sex<- lmerTest::lmer(DG_Dec~1+Sex*Part.Attractiveness*Part.Sex*agreeablenessC+(1|ID),data = subset(DG_long, sexual_orientation != "homosexual"),REML = F)
#exploratory
ModelDG_fac<- lmerTest::lmer(DG_Dec~1+Sex*Part.Attractiveness*Part.Sex+(1|ID),data = DG_long, REML = F)
ModelDG_agree<- lmerTest::lmer(DG_Dec~1+Sex*Part.Attractiveness*Part.Sex*agreeablenessC+(1|ID),data = DG_long,REML = F)
ModelDG_trust<- lmerTest::lmer(DG_Dec~1+Sex*Part.Attractiveness*Part.Sex*trustC+(1|ID),data = DG_long, REML = F)
ModelDG_mor<- lmerTest::lmer(DG_Dec~1+Sex*Part.Attractiveness*Part.Sex*moralityC+(1|ID),data = DG_long, REML = F)
ModelDG_alt<- lmerTest::lmer(DG_Dec~1+Sex*Part.Attractiveness*Part.Sex*altruismC+(1|ID),data = DG_long, REML = F)
ModelDG_coop<- lmerTest::lmer(DG_Dec~1+Sex*Part.Attractiveness*Part.Sex*cooperationC+(1|ID),data = DG_long, REML = F)
ModelDG_mod<- lmerTest::lmer(DG_Dec~1+Sex*Part.Attractiveness*Part.Sex*modestyC+(1|ID),data = DG_long, REML = F)
ModelDG_symp<- lmerTest::lmer(DG_Dec~1+Sex*Part.Attractiveness*Part.Sex*sympathyC+(1|ID),data = DG_long, REML = F)
## Results
# For the Dictator Game, the confirmatory model equals the exploratory model
models <- list(ModelDG_int, ModelDG_fac, ModelDG_agree, ModelDG_trust, ModelDG_mor, ModelDG_alt, ModelDG_coop, ModelDG_mod, ModelDG_symp)
model.names <- c('ModelDG_int', 'ModelDG_fac', 'ModelDG_agree', 'ModelDG_trust', 'ModelDG_mor', 'ModelDG_alt', 'ModelDG_coop', 'ModelDG_mod', 'ModelDG_symp')
aictab(cand.set = models, modnames = model.names, sort=T)
##
## Model selection based on AICc:
##
## K AICc Delta_AICc AICcWt Cum.Wt LL
## ModelDG_agree 26 13169.76 0.00 0.99 0.99 -6558.69
## ModelDG_mor 26 13180.58 10.82 0.00 1.00 -6564.10
## ModelDG_symp 26 13183.93 14.17 0.00 1.00 -6565.78
## ModelDG_trust 26 13190.42 20.66 0.00 1.00 -6569.02
## ModelDG_coop 26 13191.08 21.32 0.00 1.00 -6569.35
## ModelDG_alt 26 13192.46 22.70 0.00 1.00 -6570.05
## ModelDG_fac 14 13208.74 38.98 0.00 1.00 -6590.32
## ModelDG_mod 26 13213.51 43.75 0.00 1.00 -6580.57
## ModelDG_int 3 13410.06 240.29 0.00 1.00 -6702.03
car::Anova(ModelDG_agree, type=3)
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: DG_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 482.3884 1 < 2.2e-16 ***
## Sex 3.3462 1 0.067361 .
## Part.Attractiveness 19.1892 2 6.809e-05 ***
## Part.Sex 0.1327 1 0.715640
## agreeablenessC 27.7420 1 1.386e-07 ***
## Sex:Part.Attractiveness 2.0847 2 0.352620
## Sex:Part.Sex 2.0077 1 0.156501
## Part.Attractiveness:Part.Sex 7.2974 2 0.026025 *
## Sex:agreeablenessC 3.0364 1 0.081418 .
## Part.Attractiveness:agreeablenessC 1.9955 2 0.368701
## Part.Sex:agreeablenessC 2.7949 1 0.094563 .
## Sex:Part.Attractiveness:Part.Sex 13.4106 2 0.001224 **
## Sex:Part.Attractiveness:agreeablenessC 1.0928 2 0.579027
## Sex:Part.Sex:agreeablenessC 1.7211 1 0.189556
## Part.Attractiveness:Part.Sex:agreeablenessC 6.5640 2 0.037552 *
## Sex:Part.Attractiveness:Part.Sex:agreeablenessC 3.9471 2 0.138962
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
r.squaredGLMM(ModelDG_agree)
## R2m R2c
## [1,] 0.1058412 0.6538543
summary(ModelDG_agree)
## Linear mixed model fit by maximum likelihood . t-tests use Satterthwaite's
## method [lmerModLmerTest]
## Formula: DG_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * agreeablenessC +
## (1 | ID)
## Data: DG_long
##
## AIC BIC logLik deviance df.resid
## 13169.4 13331.6 -6558.7 13117.4 3754
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7867 -0.3936 -0.0051 0.3560 5.5435
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 2.469 1.571
## Residual 1.559 1.249
## Number of obs: 3780, groups: ID, 210
##
## Fixed effects:
## Estimate
## (Intercept) 4.248e+00
## Sexfemale -5.012e-01
## Part.Attractivenesshigh 2.474e-01
## Part.Attractivenesslow -2.523e-01
## Part.Sexfemale 4.155e-02
## agreeablenessC 2.110e+00
## Sexfemale:Part.Attractivenesshigh 2.219e-01
## Sexfemale:Part.Attractivenesslow 4.861e-02
## Sexfemale:Part.Sexfemale 2.290e-01
## Part.Attractivenesshigh:Part.Sexfemale 3.232e-01
## Part.Attractivenesslow:Part.Sexfemale -9.160e-02
## Sexfemale:agreeablenessC -1.110e+00
## Part.Attractivenesshigh:agreeablenessC -2.848e-01
## Part.Attractivenesslow:agreeablenessC 8.413e-03
## Part.Sexfemale:agreeablenessC -3.951e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -5.699e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 2.458e-01
## Sexfemale:Part.Attractivenesshigh:agreeablenessC -3.506e-01
## Sexfemale:Part.Attractivenesslow:agreeablenessC -3.286e-01
## Sexfemale:Part.Sexfemale:agreeablenessC 4.929e-01
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC -9.099e-02
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 6.918e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 4.134e-02
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC -8.928e-01
## Std. Error
## (Intercept) 1.934e-01
## Sexfemale 2.740e-01
## Part.Attractivenesshigh 1.141e-01
## Part.Attractivenesslow 1.141e-01
## Part.Sexfemale 1.141e-01
## agreeablenessC 4.007e-01
## Sexfemale:Part.Attractivenesshigh 1.616e-01
## Sexfemale:Part.Attractivenesslow 1.616e-01
## Sexfemale:Part.Sexfemale 1.616e-01
## Part.Attractivenesshigh:Part.Sexfemale 1.613e-01
## Part.Attractivenesslow:Part.Sexfemale 1.613e-01
## Sexfemale:agreeablenessC 6.370e-01
## Part.Attractivenesshigh:agreeablenessC 2.363e-01
## Part.Attractivenesslow:agreeablenessC 2.363e-01
## Part.Sexfemale:agreeablenessC 2.363e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 2.285e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 2.285e-01
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 3.757e-01
## Sexfemale:Part.Attractivenesslow:agreeablenessC 3.757e-01
## Sexfemale:Part.Sexfemale:agreeablenessC 3.757e-01
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 3.342e-01
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 3.342e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 5.313e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 5.313e-01
## df
## (Intercept) 2.867e+02
## Sexfemale 2.867e+02
## Part.Attractivenesshigh 3.570e+03
## Part.Attractivenesslow 3.570e+03
## Part.Sexfemale 3.570e+03
## agreeablenessC 2.867e+02
## Sexfemale:Part.Attractivenesshigh 3.570e+03
## Sexfemale:Part.Attractivenesslow 3.570e+03
## Sexfemale:Part.Sexfemale 3.570e+03
## Part.Attractivenesshigh:Part.Sexfemale 3.570e+03
## Part.Attractivenesslow:Part.Sexfemale 3.570e+03
## Sexfemale:agreeablenessC 2.867e+02
## Part.Attractivenesshigh:agreeablenessC 3.570e+03
## Part.Attractivenesslow:agreeablenessC 3.570e+03
## Part.Sexfemale:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 3.570e+03
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 3.570e+03
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesslow:agreeablenessC 3.570e+03
## Sexfemale:Part.Sexfemale:agreeablenessC 3.570e+03
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 3.570e+03
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 3.570e+03
## t value
## (Intercept) 21.963
## Sexfemale -1.829
## Part.Attractivenesshigh 2.169
## Part.Attractivenesslow -2.212
## Part.Sexfemale 0.364
## agreeablenessC 5.267
## Sexfemale:Part.Attractivenesshigh 1.373
## Sexfemale:Part.Attractivenesslow 0.301
## Sexfemale:Part.Sexfemale 1.417
## Part.Attractivenesshigh:Part.Sexfemale 2.003
## Part.Attractivenesslow:Part.Sexfemale -0.568
## Sexfemale:agreeablenessC -1.743
## Part.Attractivenesshigh:agreeablenessC -1.205
## Part.Attractivenesslow:agreeablenessC 0.036
## Part.Sexfemale:agreeablenessC -1.672
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -2.494
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 1.076
## Sexfemale:Part.Attractivenesshigh:agreeablenessC -0.933
## Sexfemale:Part.Attractivenesslow:agreeablenessC -0.875
## Sexfemale:Part.Sexfemale:agreeablenessC 1.312
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC -0.272
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 2.070
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.078
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC -1.680
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## Sexfemale 0.0684 .
## Part.Attractivenesshigh 0.0302 *
## Part.Attractivenesslow 0.0271 *
## Part.Sexfemale 0.7157
## agreeablenessC 2.73e-07 ***
## Sexfemale:Part.Attractivenesshigh 0.1697
## Sexfemale:Part.Attractivenesslow 0.7636
## Sexfemale:Part.Sexfemale 0.1566
## Part.Attractivenesshigh:Part.Sexfemale 0.0452 *
## Part.Attractivenesslow:Part.Sexfemale 0.5702
## Sexfemale:agreeablenessC 0.0825 .
## Part.Attractivenesshigh:agreeablenessC 0.2282
## Part.Attractivenesslow:agreeablenessC 0.9716
## Part.Sexfemale:agreeablenessC 0.0947 .
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.0127 *
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.2821
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 0.3508
## Sexfemale:Part.Attractivenesslow:agreeablenessC 0.3818
## Sexfemale:Part.Sexfemale:agreeablenessC 0.1896
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.7854
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.0385 *
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.9380
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.0930 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation matrix not shown by default, as p = 24 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
# Part.Attractiveness
emms <- emmeans(ModelDG_agree, ~ Part.Attractiveness)
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness_pairwise estimate SE df z.ratio p.value
## moderate - high -0.377 0.0571 Inf -6.607 <.0001
## moderate - low 0.212 0.0571 Inf 3.716 0.0006
## high - low 0.590 0.0571 Inf 10.323 <.0001
##
## Results are averaged over the levels of: Sex, Part.Sex
## Degrees-of-freedom method: asymptotic
## P value adjustment: bonferroni method for 3 tests
# Part.Sex*Part.Attractiveness
emms <- emmeans(ModelDG_agree, ~ Part.Sex|Part.Attractiveness)
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness = moderate:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.156 0.0808 Inf -1.931 0.0535
##
## Part.Attractiveness = high:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.194 0.0808 Inf -2.404 0.0162
##
## Part.Attractiveness = low:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.187 0.0808 Inf -2.319 0.0204
##
## Results are averaged over the levels of: Sex
## Degrees-of-freedom method: asymptotic
# Participant Sex*Part.Sex*Part.Attractiveness
emms <- emmeans(ModelDG_agree, ~ Part.Attractiveness*Part.Sex|Sex)
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Sex = male:
## Part.Attractiveness_pairwise Part.Sex_pairwise estimate SE df z.ratio
## moderate - high male - female 0.3232 0.161 Inf 2.003
## moderate - low male - female -0.0916 0.161 Inf -0.568
## high - low male - female -0.4148 0.161 Inf -2.571
## p.value
## 0.1354
## 1.0000
## 0.0304
##
## Sex = female:
## Part.Attractiveness_pairwise Part.Sex_pairwise estimate SE df z.ratio
## moderate - high male - female -0.2467 0.162 Inf -1.524
## moderate - low male - female 0.1542 0.162 Inf 0.953
## high - low male - female 0.4010 0.162 Inf 2.477
## p.value
## 0.3824
## 1.0000
## 0.0398
##
## Degrees-of-freedom method: asymptotic
## P value adjustment: bonferroni method for 3 tests
#P art.Sex*Part.Attractiveness*Agreeableness
emtrends(ModelDG_agree, pairwise ~ Part.Attractiveness|Part.Sex, var = "agreeablenessC", adjust = "bonferroni")
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## NOTE: Results may be misleading due to involvement in interactions
## $emtrends
## Part.Sex = male:
## Part.Attractiveness agreeablenessC.trend SE df asymp.LCL asymp.UCL
## moderate 1.555 0.318 Inf 0.931 2.18
## high 1.095 0.318 Inf 0.471 1.72
## low 1.399 0.318 Inf 0.775 2.02
##
## Part.Sex = female:
## Part.Attractiveness agreeablenessC.trend SE df asymp.LCL asymp.UCL
## moderate 1.407 0.318 Inf 0.783 2.03
## high 0.876 0.318 Inf 0.252 1.50
## low 1.496 0.318 Inf 0.872 2.12
##
## Results are averaged over the levels of: Sex
## Degrees-of-freedom method: asymptotic
## Confidence level used: 0.95
##
## $contrasts
## Part.Sex = male:
## contrast estimate SE df z.ratio p.value
## moderate - high 0.4601 0.188 Inf 2.449 0.0429
## moderate - low 0.1559 0.188 Inf 0.830 1.0000
## high - low -0.3042 0.188 Inf -1.619 0.3161
##
## Part.Sex = female:
## contrast estimate SE df z.ratio p.value
## moderate - high 0.5304 0.188 Inf 2.824 0.0142
## moderate - low -0.0895 0.188 Inf -0.477 1.0000
## high - low -0.6199 0.188 Inf -3.300 0.0029
##
## Results are averaged over the levels of: Sex
## Degrees-of-freedom method: asymptotic
## P value adjustment: bonferroni method for 3 tests
# check if confirmatory results are stable withouth homosexual individuals
car::Anova(ModelDG_agree_sex, type=3)
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: DG_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 426.3316 1 < 2.2e-16 ***
## Sex 2.3092 1 0.12861
## Part.Attractiveness 20.5075 2 3.522e-05 ***
## Part.Sex 0.6831 1 0.40852
## agreeablenessC 23.5563 1 1.213e-06 ***
## Sex:Part.Attractiveness 0.2003 2 0.90471
## Sex:Part.Sex 1.0375 1 0.30839
## Part.Attractiveness:Part.Sex 4.8205 2 0.08979 .
## Sex:agreeablenessC 2.1695 1 0.14077
## Part.Attractiveness:agreeablenessC 2.2817 2 0.31954
## Part.Sex:agreeablenessC 1.8655 1 0.17199
## Sex:Part.Attractiveness:Part.Sex 8.9606 2 0.01133 *
## Sex:Part.Attractiveness:agreeablenessC 2.3635 2 0.30675
## Sex:Part.Sex:agreeablenessC 1.2421 1 0.26507
## Part.Attractiveness:Part.Sex:agreeablenessC 8.5129 2 0.01417 *
## Sex:Part.Attractiveness:Part.Sex:agreeablenessC 4.4165 2 0.10989
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# Trust Game
load("TG.Rda")
TG_long$Sex <- relevel(TG_long$Sex, ref = "male")
TG_long$Part.Sex <- relevel(TG_long$Part.Sex, ref = "male")
## Models
# baseline model
ModelTG_int<- lmerTest::lmer(TG_Dec~1+(1|ID),data = TG_long, REML = F)
# onfirmatory
ModelTG_agree<- lmerTest::lmer(TG_Dec~1+Sex*Part.Attractiveness*Part.Sex*agreeablenessC+(1|ID),data = TG_long, REML = F)
# without homosexual individuals
ModelTG_agree_sex<- lmerTest::lmer(TG_Dec~1+Sex*Part.Attractiveness*Part.Sex*agreeablenessC+(1|ID),data = subset(TG_long, sexual_orientation != "homosexual"),REML = F)
# exploratory
ModelTG_fac<- lmerTest::lmer(TG_Dec~1+Sex*Part.Attractiveness*Part.Sex+(1|ID),data = TG_long, REML = F)
ModelTG_trust<- lmerTest::lmer(TG_Dec~1+Sex*Part.Attractiveness*Part.Sex*trustC+(1|ID),data = TG_long, REML = F)
ModelTG_mor<- lmerTest::lmer(TG_Dec~1+Sex*Part.Attractiveness*Part.Sex*moralityC+(1|ID),data = TG_long, REML = F)
ModelTG_alt<- lmerTest::lmer(TG_Dec~1+Sex*Part.Attractiveness*Part.Sex*altruismC+(1|ID),data = TG_long, REML = F)
ModelTG_coop<- lmerTest::lmer(TG_Dec~1+Sex*Part.Attractiveness*Part.Sex*cooperationC+(1|ID),data = TG_long, REML = F)
ModelTG_mod<- lmerTest::lmer(TG_Dec~1+Sex*Part.Attractiveness*Part.Sex*modestyC+(1|ID),data = TG_long, REML = F)
ModelTG_symp<- lmerTest::lmer(TG_Dec~1+Sex*Part.Attractiveness*Part.Sex*sympathyC+(1|ID),data = TG_long, REML = F)
## Results
### Confirmatory
summary(ModelTG_agree)
## Linear mixed model fit by maximum likelihood . t-tests use Satterthwaite's
## method [lmerModLmerTest]
## Formula: TG_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * agreeablenessC +
## (1 | ID)
## Data: TG_long
##
## AIC BIC logLik deviance df.resid
## 14954.3 15116.5 -7451.1 14902.3 3754
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.8383 -0.4849 -0.0357 0.4461 5.5490
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 4.369 2.090
## Residual 2.487 1.577
## Number of obs: 3780, groups: ID, 210
##
## Fixed effects:
## Estimate
## (Intercept) 4.920e+00
## Sexfemale -8.444e-01
## Part.Attractivenesshigh 6.601e-01
## Part.Attractivenesslow -1.462e-01
## Part.Sexfemale 3.577e-01
## agreeablenessC 1.686e+00
## Sexfemale:Part.Attractivenesshigh 4.239e-02
## Sexfemale:Part.Attractivenesslow -1.068e-01
## Sexfemale:Part.Sexfemale 1.499e-01
## Part.Attractivenesshigh:Part.Sexfemale -1.230e-01
## Part.Attractivenesslow:Part.Sexfemale -5.902e-01
## Sexfemale:agreeablenessC -1.128e+00
## Part.Attractivenesshigh:agreeablenessC 1.490e-02
## Part.Attractivenesslow:agreeablenessC -4.358e-03
## Part.Sexfemale:agreeablenessC 3.348e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -2.616e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 5.514e-02
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 6.628e-01
## Sexfemale:Part.Attractivenesslow:agreeablenessC -2.244e-01
## Sexfemale:Part.Sexfemale:agreeablenessC 5.443e-02
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC -6.771e-01
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC -1.323e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 4.938e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 4.610e-01
## Std. Error
## (Intercept) 2.551e-01
## Sexfemale 3.613e-01
## Part.Attractivenesshigh 1.440e-01
## Part.Attractivenesslow 1.440e-01
## Part.Sexfemale 1.440e-01
## agreeablenessC 5.284e-01
## Sexfemale:Part.Attractivenesshigh 2.041e-01
## Sexfemale:Part.Attractivenesslow 2.041e-01
## Sexfemale:Part.Sexfemale 2.041e-01
## Part.Attractivenesshigh:Part.Sexfemale 2.037e-01
## Part.Attractivenesslow:Part.Sexfemale 2.037e-01
## Sexfemale:agreeablenessC 8.400e-01
## Part.Attractivenesshigh:agreeablenessC 2.984e-01
## Part.Attractivenesslow:agreeablenessC 2.984e-01
## Part.Sexfemale:agreeablenessC 2.984e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 2.886e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 2.886e-01
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 4.744e-01
## Sexfemale:Part.Attractivenesslow:agreeablenessC 4.744e-01
## Sexfemale:Part.Sexfemale:agreeablenessC 4.744e-01
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 4.220e-01
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 4.220e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 6.709e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 6.709e-01
## df
## (Intercept) 2.789e+02
## Sexfemale 2.789e+02
## Part.Attractivenesshigh 3.570e+03
## Part.Attractivenesslow 3.570e+03
## Part.Sexfemale 3.570e+03
## agreeablenessC 2.789e+02
## Sexfemale:Part.Attractivenesshigh 3.570e+03
## Sexfemale:Part.Attractivenesslow 3.570e+03
## Sexfemale:Part.Sexfemale 3.570e+03
## Part.Attractivenesshigh:Part.Sexfemale 3.570e+03
## Part.Attractivenesslow:Part.Sexfemale 3.570e+03
## Sexfemale:agreeablenessC 2.789e+02
## Part.Attractivenesshigh:agreeablenessC 3.570e+03
## Part.Attractivenesslow:agreeablenessC 3.570e+03
## Part.Sexfemale:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 3.570e+03
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 3.570e+03
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesslow:agreeablenessC 3.570e+03
## Sexfemale:Part.Sexfemale:agreeablenessC 3.570e+03
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 3.570e+03
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 3.570e+03
## t value
## (Intercept) 19.290
## Sexfemale -2.337
## Part.Attractivenesshigh 4.582
## Part.Attractivenesslow -1.015
## Part.Sexfemale 2.483
## agreeablenessC 3.191
## Sexfemale:Part.Attractivenesshigh 0.208
## Sexfemale:Part.Attractivenesslow -0.523
## Sexfemale:Part.Sexfemale 0.734
## Part.Attractivenesshigh:Part.Sexfemale -0.604
## Part.Attractivenesslow:Part.Sexfemale -2.898
## Sexfemale:agreeablenessC -1.342
## Part.Attractivenesshigh:agreeablenessC 0.050
## Part.Attractivenesslow:agreeablenessC -0.015
## Part.Sexfemale:agreeablenessC 1.122
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -0.906
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.191
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 1.397
## Sexfemale:Part.Attractivenesslow:agreeablenessC -0.473
## Sexfemale:Part.Sexfemale:agreeablenessC 0.115
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC -1.604
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC -0.313
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.736
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.687
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## Sexfemale 0.02015 *
## Part.Attractivenesshigh 4.75e-06 ***
## Part.Attractivenesslow 0.31025
## Part.Sexfemale 0.01306 *
## agreeablenessC 0.00158 **
## Sexfemale:Part.Attractivenesshigh 0.83546
## Sexfemale:Part.Attractivenesslow 0.60091
## Sexfemale:Part.Sexfemale 0.46271
## Part.Attractivenesshigh:Part.Sexfemale 0.54608
## Part.Attractivenesslow:Part.Sexfemale 0.00378 **
## Sexfemale:agreeablenessC 0.18057
## Part.Attractivenesshigh:agreeablenessC 0.96019
## Part.Attractivenesslow:agreeablenessC 0.98835
## Part.Sexfemale:agreeablenessC 0.26189
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.36478
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.84849
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 0.16246
## Sexfemale:Part.Attractivenesslow:agreeablenessC 0.63621
## Sexfemale:Part.Sexfemale:agreeablenessC 0.90866
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.10870
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.75397
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.46177
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.49200
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation matrix not shown by default, as p = 24 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
car::Anova(ModelTG_agree, type=3)
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: TG_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 372.0864 1 < 2.2e-16 ***
## Sex 5.4613 1 0.019442 *
## Part.Attractiveness 35.5722 2 1.886e-08 ***
## Part.Sex 6.1671 1 0.013015 *
## agreeablenessC 10.1828 1 0.001418 **
## Sex:Part.Attractiveness 0.5673 2 0.753023
## Sex:Part.Sex 0.5395 1 0.462658
## Part.Attractiveness:Part.Sex 9.3480 2 0.009335 **
## Sex:agreeablenessC 1.8019 1 0.179478
## Part.Attractiveness:agreeablenessC 0.0046 2 0.997713
## Part.Sex:agreeablenessC 1.2591 1 0.261814
## Sex:Part.Attractiveness:Part.Sex 1.3750 2 0.502828
## Sex:Part.Attractiveness:agreeablenessC 3.7821 2 0.150911
## Sex:Part.Sex:agreeablenessC 0.0132 1 0.908656
## Part.Attractiveness:Part.Sex:agreeablenessC 2.8928 2 0.235416
## Sex:Part.Attractiveness:Part.Sex:agreeablenessC 0.6776 2 0.712636
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
r.squaredGLMM(ModelTG_agree)
## R2m R2c
## [1,] 0.07843979 0.6657333
summary(ModelTG_agree)
## Linear mixed model fit by maximum likelihood . t-tests use Satterthwaite's
## method [lmerModLmerTest]
## Formula: TG_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * agreeablenessC +
## (1 | ID)
## Data: TG_long
##
## AIC BIC logLik deviance df.resid
## 14954.3 15116.5 -7451.1 14902.3 3754
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.8383 -0.4849 -0.0357 0.4461 5.5490
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 4.369 2.090
## Residual 2.487 1.577
## Number of obs: 3780, groups: ID, 210
##
## Fixed effects:
## Estimate
## (Intercept) 4.920e+00
## Sexfemale -8.444e-01
## Part.Attractivenesshigh 6.601e-01
## Part.Attractivenesslow -1.462e-01
## Part.Sexfemale 3.577e-01
## agreeablenessC 1.686e+00
## Sexfemale:Part.Attractivenesshigh 4.239e-02
## Sexfemale:Part.Attractivenesslow -1.068e-01
## Sexfemale:Part.Sexfemale 1.499e-01
## Part.Attractivenesshigh:Part.Sexfemale -1.230e-01
## Part.Attractivenesslow:Part.Sexfemale -5.902e-01
## Sexfemale:agreeablenessC -1.128e+00
## Part.Attractivenesshigh:agreeablenessC 1.490e-02
## Part.Attractivenesslow:agreeablenessC -4.358e-03
## Part.Sexfemale:agreeablenessC 3.348e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -2.616e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 5.514e-02
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 6.628e-01
## Sexfemale:Part.Attractivenesslow:agreeablenessC -2.244e-01
## Sexfemale:Part.Sexfemale:agreeablenessC 5.443e-02
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC -6.771e-01
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC -1.323e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 4.938e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 4.610e-01
## Std. Error
## (Intercept) 2.551e-01
## Sexfemale 3.613e-01
## Part.Attractivenesshigh 1.440e-01
## Part.Attractivenesslow 1.440e-01
## Part.Sexfemale 1.440e-01
## agreeablenessC 5.284e-01
## Sexfemale:Part.Attractivenesshigh 2.041e-01
## Sexfemale:Part.Attractivenesslow 2.041e-01
## Sexfemale:Part.Sexfemale 2.041e-01
## Part.Attractivenesshigh:Part.Sexfemale 2.037e-01
## Part.Attractivenesslow:Part.Sexfemale 2.037e-01
## Sexfemale:agreeablenessC 8.400e-01
## Part.Attractivenesshigh:agreeablenessC 2.984e-01
## Part.Attractivenesslow:agreeablenessC 2.984e-01
## Part.Sexfemale:agreeablenessC 2.984e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 2.886e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 2.886e-01
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 4.744e-01
## Sexfemale:Part.Attractivenesslow:agreeablenessC 4.744e-01
## Sexfemale:Part.Sexfemale:agreeablenessC 4.744e-01
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 4.220e-01
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 4.220e-01
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 6.709e-01
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 6.709e-01
## df
## (Intercept) 2.789e+02
## Sexfemale 2.789e+02
## Part.Attractivenesshigh 3.570e+03
## Part.Attractivenesslow 3.570e+03
## Part.Sexfemale 3.570e+03
## agreeablenessC 2.789e+02
## Sexfemale:Part.Attractivenesshigh 3.570e+03
## Sexfemale:Part.Attractivenesslow 3.570e+03
## Sexfemale:Part.Sexfemale 3.570e+03
## Part.Attractivenesshigh:Part.Sexfemale 3.570e+03
## Part.Attractivenesslow:Part.Sexfemale 3.570e+03
## Sexfemale:agreeablenessC 2.789e+02
## Part.Attractivenesshigh:agreeablenessC 3.570e+03
## Part.Attractivenesslow:agreeablenessC 3.570e+03
## Part.Sexfemale:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 3.570e+03
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 3.570e+03
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesslow:agreeablenessC 3.570e+03
## Sexfemale:Part.Sexfemale:agreeablenessC 3.570e+03
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 3.570e+03
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 3.570e+03
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 3.570e+03
## t value
## (Intercept) 19.290
## Sexfemale -2.337
## Part.Attractivenesshigh 4.582
## Part.Attractivenesslow -1.015
## Part.Sexfemale 2.483
## agreeablenessC 3.191
## Sexfemale:Part.Attractivenesshigh 0.208
## Sexfemale:Part.Attractivenesslow -0.523
## Sexfemale:Part.Sexfemale 0.734
## Part.Attractivenesshigh:Part.Sexfemale -0.604
## Part.Attractivenesslow:Part.Sexfemale -2.898
## Sexfemale:agreeablenessC -1.342
## Part.Attractivenesshigh:agreeablenessC 0.050
## Part.Attractivenesslow:agreeablenessC -0.015
## Part.Sexfemale:agreeablenessC 1.122
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -0.906
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.191
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 1.397
## Sexfemale:Part.Attractivenesslow:agreeablenessC -0.473
## Sexfemale:Part.Sexfemale:agreeablenessC 0.115
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC -1.604
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC -0.313
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.736
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.687
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## Sexfemale 0.02015 *
## Part.Attractivenesshigh 4.75e-06 ***
## Part.Attractivenesslow 0.31025
## Part.Sexfemale 0.01306 *
## agreeablenessC 0.00158 **
## Sexfemale:Part.Attractivenesshigh 0.83546
## Sexfemale:Part.Attractivenesslow 0.60091
## Sexfemale:Part.Sexfemale 0.46271
## Part.Attractivenesshigh:Part.Sexfemale 0.54608
## Part.Attractivenesslow:Part.Sexfemale 0.00378 **
## Sexfemale:agreeablenessC 0.18057
## Part.Attractivenesshigh:agreeablenessC 0.96019
## Part.Attractivenesslow:agreeablenessC 0.98835
## Part.Sexfemale:agreeablenessC 0.26189
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.36478
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.84849
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 0.16246
## Sexfemale:Part.Attractivenesslow:agreeablenessC 0.63621
## Sexfemale:Part.Sexfemale:agreeablenessC 0.90866
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.10870
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.75397
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.46177
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.49200
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation matrix not shown by default, as p = 24 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
# Part.Attractiveness
emms <- emmeans(ModelTG_agree, ~ Part.Attractiveness)
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness_pairwise estimate SE df z.ratio p.value
## moderate - high -0.554 0.0721 Inf -7.684 <.0001
## moderate - low 0.481 0.0721 Inf 6.665 <.0001
## high - low 1.035 0.0721 Inf 14.349 <.0001
##
## Results are averaged over the levels of: Sex, Part.Sex
## Degrees-of-freedom method: asymptotic
## P value adjustment: bonferroni method for 3 tests
# Part.Sex
emms <- emmeans(ModelTG_agree, ~ Part.Sex)
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.16 0.0589 Inf -2.725 0.0064
##
## Results are averaged over the levels of: Sex, Part.Attractiveness
## Degrees-of-freedom method: asymptotic
# Participant Sex
emms <- emmeans(ModelTG_agree, ~ Sex)
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Sex_pairwise estimate SE df z.ratio p.value
## male - female 0.825 0.336 Inf 2.453 0.0142
##
## Results are averaged over the levels of: Part.Attractiveness, Part.Sex
## Degrees-of-freedom method: asymptotic
# Part.Attractiveness*Part.Sex
emms <- emmeans(ModelTG_agree, ~ Part.Sex|Part.Attractiveness)
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness = moderate:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.433 0.102 Inf -4.240 <.0001
##
## Part.Attractiveness = high:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.179 0.102 Inf -1.753 0.0796
##
## Part.Attractiveness = low:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female 0.130 0.102 Inf 1.274 0.2025
##
## Results are averaged over the levels of: Sex
## Degrees-of-freedom method: asymptotic
# check if confirmatory results are stable without homosexual individuals
car::Anova(ModelTG_agree_sex, type=3)
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: TG_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 328.1021 1 < 2.2e-16 ***
## Sex 4.8915 1 0.026990 *
## Part.Attractiveness 33.8027 2 4.569e-08 ***
## Part.Sex 6.1386 1 0.013226 *
## agreeablenessC 10.6208 1 0.001118 **
## Sex:Part.Attractiveness 1.6539 2 0.437385
## Sex:Part.Sex 0.3676 1 0.544336
## Part.Attractiveness:Part.Sex 10.4254 2 0.005447 **
## Sex:agreeablenessC 2.3430 1 0.125845
## Part.Attractiveness:agreeablenessC 0.3201 2 0.852111
## Part.Sex:agreeablenessC 0.6368 1 0.424876
## Sex:Part.Attractiveness:Part.Sex 0.9100 2 0.634441
## Sex:Part.Attractiveness:agreeablenessC 5.0896 2 0.078490 .
## Sex:Part.Sex:agreeablenessC 0.0413 1 0.838988
## Part.Attractiveness:Part.Sex:agreeablenessC 2.6146 2 0.270544
## Sex:Part.Attractiveness:Part.Sex:agreeablenessC 0.9214 2 0.630844
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
### Exploratory
models2 <- list(ModelTG_int, ModelTG_fac, ModelTG_agree, ModelTG_trust, ModelTG_mor, ModelTG_alt, ModelTG_coop, ModelTG_mod, ModelTG_symp)
model.names2 <- c('ModelTG_int', 'ModelTG_fac', 'ModelTG_agree', 'ModelTG_trust', 'ModelTG_mor', 'ModelTG_alt', 'ModelTG_coop', 'ModelTG_mod', 'ModelTG_symp')
aictab(cand.set = models2, modnames = model.names2, sort =T)
##
## Model selection based on AICc:
##
## K AICc Delta_AICc AICcWt Cum.Wt LL
## ModelTG_symp 26 14949.47 0.00 0.54 0.54 -7448.55
## ModelTG_alt 26 14950.00 0.53 0.41 0.96 -7448.81
## ModelTG_agree 26 14954.67 5.20 0.04 1.00 -7451.15
## ModelTG_trust 26 14959.92 10.46 0.00 1.00 -7453.78
## ModelTG_fac 14 14962.86 13.39 0.00 1.00 -7467.37
## ModelTG_coop 26 14966.28 16.82 0.00 1.00 -7456.95
## ModelTG_mor 26 14972.95 23.48 0.00 1.00 -7460.29
## ModelTG_mod 26 14973.20 23.74 0.00 1.00 -7460.42
## ModelTG_int 3 15290.03 340.56 0.00 1.00 -7642.01
anova(ModelTG_symp, ModelTG_alt)
## Data: TG_long
## Models:
## ModelTG_symp: TG_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * sympathyC + (1 | ID)
## ModelTG_alt: TG_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * altruismC + (1 | ID)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## ModelTG_symp 26 14949 15111 -7448.5 14897
## ModelTG_alt 26 14950 15112 -7448.8 14898 0 0
car::Anova(ModelTG_symp, type=3)
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: TG_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 389.1078 1 < 2.2e-16 ***
## Sex 5.2136 1 0.0224109 *
## Part.Attractiveness 35.2740 2 2.19e-08 ***
## Part.Sex 7.1760 1 0.0073885 **
## sympathyC 11.0648 1 0.0008798 ***
## Sex:Part.Attractiveness 0.9229 2 0.6303705
## Sex:Part.Sex 1.1237 1 0.2891129
## Part.Attractiveness:Part.Sex 9.2067 2 0.0100184 *
## Sex:sympathyC 2.3438 1 0.1257857
## Part.Attractiveness:sympathyC 0.3346 2 0.8459395
## Part.Sex:sympathyC 2.6014 1 0.1067700
## Sex:Part.Attractiveness:Part.Sex 0.7586 2 0.6843405
## Sex:Part.Attractiveness:sympathyC 6.2158 2 0.0446945 *
## Sex:Part.Sex:sympathyC 1.0299 1 0.3101783
## Part.Attractiveness:Part.Sex:sympathyC 2.3279 2 0.3122558
## Sex:Part.Attractiveness:Part.Sex:sympathyC 2.1127 2 0.3477186
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
r.squaredGLMM(ModelTG_symp)
## R2m R2c
## [1,] 0.08160054 0.6661298
summary(ModelTG_symp)
## Linear mixed model fit by maximum likelihood . t-tests use Satterthwaite's
## method [lmerModLmerTest]
## Formula: TG_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * sympathyC +
## (1 | ID)
## Data: TG_long
##
## AIC BIC logLik deviance df.resid
## 14949.1 15111.3 -7448.5 14897.1 3754
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9163 -0.4780 -0.0424 0.4481 5.4645
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 4.348 2.085
## Residual 2.484 1.576
## Number of obs: 3780, groups: ID, 210
##
## Fixed effects:
## Estimate
## (Intercept) 4.87951
## Sexfemale -0.78742
## Part.Attractivenesshigh 0.62419
## Part.Attractivenesslow -0.16291
## Part.Sexfemale 0.37478
## sympathyC 1.23196
## Sexfemale:Part.Attractivenesshigh 0.09612
## Sexfemale:Part.Attractivenesslow -0.09123
## Sexfemale:Part.Sexfemale 0.20676
## Part.Attractivenesshigh:Part.Sexfemale -0.07488
## Part.Attractivenesslow:Part.Sexfemale -0.55330
## Sexfemale:sympathyC -0.84108
## Part.Attractivenesshigh:sympathyC -0.12102
## Part.Attractivenesslow:sympathyC -0.06572
## Part.Sexfemale:sympathyC 0.33785
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -0.22673
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale -0.04456
## Sexfemale:Part.Attractivenesshigh:sympathyC 0.60478
## Sexfemale:Part.Attractivenesslow:sympathyC -0.11688
## Sexfemale:Part.Sexfemale:sympathyC -0.31534
## Part.Attractivenesshigh:Part.Sexfemale:sympathyC -0.37621
## Part.Attractivenesslow:Part.Sexfemale:sympathyC 0.02883
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:sympathyC -0.10650
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:sympathyC 0.49215
## Std. Error
## (Intercept) 0.24737
## Sexfemale 0.34485
## Part.Attractivenesshigh 0.13991
## Part.Attractivenesslow 0.13991
## Part.Sexfemale 0.13991
## sympathyC 0.37036
## Sexfemale:Part.Attractivenesshigh 0.19504
## Sexfemale:Part.Attractivenesslow 0.19504
## Sexfemale:Part.Sexfemale 0.19504
## Part.Attractivenesshigh:Part.Sexfemale 0.19786
## Part.Attractivenesslow:Part.Sexfemale 0.19786
## Sexfemale:sympathyC 0.54939
## Part.Attractivenesshigh:sympathyC 0.20947
## Part.Attractivenesslow:sympathyC 0.20947
## Part.Sexfemale:sympathyC 0.20947
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.27583
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.27583
## Sexfemale:Part.Attractivenesshigh:sympathyC 0.31073
## Sexfemale:Part.Attractivenesslow:sympathyC 0.31073
## Sexfemale:Part.Sexfemale:sympathyC 0.31073
## Part.Attractivenesshigh:Part.Sexfemale:sympathyC 0.29623
## Part.Attractivenesslow:Part.Sexfemale:sympathyC 0.29623
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:sympathyC 0.43943
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:sympathyC 0.43943
## df t value
## (Intercept) 279.16577 19.726
## Sexfemale 279.16577 -2.283
## Part.Attractivenesshigh 3570.00000 4.461
## Part.Attractivenesslow 3570.00000 -1.164
## Part.Sexfemale 3570.00000 2.679
## sympathyC 279.16577 3.326
## Sexfemale:Part.Attractivenesshigh 3570.00000 0.493
## Sexfemale:Part.Attractivenesslow 3570.00000 -0.468
## Sexfemale:Part.Sexfemale 3570.00000 1.060
## Part.Attractivenesshigh:Part.Sexfemale 3570.00000 -0.378
## Part.Attractivenesslow:Part.Sexfemale 3570.00000 -2.796
## Sexfemale:sympathyC 279.16577 -1.531
## Part.Attractivenesshigh:sympathyC 3570.00000 -0.578
## Part.Attractivenesslow:sympathyC 3570.00000 -0.314
## Part.Sexfemale:sympathyC 3570.00000 1.613
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 3570.00000 -0.822
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 3570.00000 -0.162
## Sexfemale:Part.Attractivenesshigh:sympathyC 3570.00000 1.946
## Sexfemale:Part.Attractivenesslow:sympathyC 3570.00000 -0.376
## Sexfemale:Part.Sexfemale:sympathyC 3570.00000 -1.015
## Part.Attractivenesshigh:Part.Sexfemale:sympathyC 3570.00000 -1.270
## Part.Attractivenesslow:Part.Sexfemale:sympathyC 3570.00000 0.097
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:sympathyC 3570.00000 -0.242
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:sympathyC 3570.00000 1.120
## Pr(>|t|)
## (Intercept) < 2e-16 ***
## Sexfemale 0.023162 *
## Part.Attractivenesshigh 8.39e-06 ***
## Part.Attractivenesslow 0.244335
## Part.Sexfemale 0.007422 **
## sympathyC 0.000998 ***
## Sexfemale:Part.Attractivenesshigh 0.622185
## Sexfemale:Part.Attractivenesslow 0.639980
## Sexfemale:Part.Sexfemale 0.289185
## Part.Attractivenesshigh:Part.Sexfemale 0.705124
## Part.Attractivenesslow:Part.Sexfemale 0.005195 **
## Sexfemale:sympathyC 0.126918
## Part.Attractivenesshigh:sympathyC 0.563473
## Part.Attractivenesslow:sympathyC 0.753716
## Part.Sexfemale:sympathyC 0.106858
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.411150
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.871683
## Sexfemale:Part.Attractivenesshigh:sympathyC 0.051692 .
## Sexfemale:Part.Attractivenesslow:sympathyC 0.706829
## Sexfemale:Part.Sexfemale:sympathyC 0.310247
## Part.Attractivenesshigh:Part.Sexfemale:sympathyC 0.204176
## Part.Attractivenesslow:Part.Sexfemale:sympathyC 0.922481
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:sympathyC 0.808509
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:sympathyC 0.262798
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation matrix not shown by default, as p = 24 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
# Part.Attractiveness*Part.Sex
emms <- emmeans(ModelTG_symp, ~ Part.Sex|Part.Attractiveness)
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness = moderate:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.4782 0.0975 Inf -4.903 <.0001
##
## Part.Attractiveness = high:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.2899 0.0975 Inf -2.973 0.0030
##
## Part.Attractiveness = low:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female 0.0974 0.0975 Inf 0.999 0.3179
##
## Results are averaged over the levels of: Sex
## Degrees-of-freedom method: asymptotic
# Participant Sex*Part.Attractiveness*Trait
emtrends(ModelTG_symp, pairwise ~ Part.Attractiveness|Sex, var = "sympathyC", adjust = "bonferroni")
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## NOTE: Results may be misleading due to involvement in interactions
## $emtrends
## Sex = male:
## Part.Attractiveness sympathyC.trend SE df asymp.LCL asymp.UCL
## moderate 1.401 0.355 Inf 0.705 2.10
## high 1.092 0.355 Inf 0.395 1.79
## low 1.350 0.355 Inf 0.653 2.05
##
## Sex = female:
## Part.Attractiveness sympathyC.trend SE df asymp.LCL asymp.UCL
## moderate 0.402 0.389 Inf -0.361 1.16
## high 0.645 0.389 Inf -0.118 1.41
## low 0.480 0.389 Inf -0.283 1.24
##
## Results are averaged over the levels of: Part.Sex
## Degrees-of-freedom method: asymptotic
## Confidence level used: 0.95
##
## $contrasts
## Sex = male:
## contrast estimate SE df z.ratio p.value
## moderate - high 0.3091 0.148 Inf 2.087 0.1107
## moderate - low 0.0513 0.148 Inf 0.346 1.0000
## high - low -0.2578 0.148 Inf -1.741 0.2453
##
## Sex = female:
## contrast estimate SE df z.ratio p.value
## moderate - high -0.2424 0.162 Inf -1.494 0.4058
## moderate - low -0.0779 0.162 Inf -0.480 1.0000
## high - low 0.1645 0.162 Inf 1.014 0.9321
##
## Results are averaged over the levels of: Part.Sex
## Degrees-of-freedom method: asymptotic
## P value adjustment: bonferroni method for 3 tests
# Participant Sex*Part.Attractiveness*Part.Sex*Trait
emtrends(ModelTG_symp, pairwise ~ Sex|Part.Attractiveness|Part.Sex, var = "sympathyC", adjust = "bonferroni")
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'pbkrtest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(pbkrtest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## Note: D.f. calculations have been disabled because the number of observations exceeds 3000.
## To enable adjustments, add the argument 'lmerTest.limit = 3780' (or larger)
## [or, globally, 'set emm_options(lmerTest.limit = 3780)' or larger];
## but be warned that this may result in large computation time and memory use.
## $emtrends
## Part.Attractiveness = moderate, Part.Sex = male:
## Sex sympathyC.trend SE df asymp.LCL asymp.UCL
## male 1.232 0.370 Inf 0.5061 1.96
## female 0.391 0.406 Inf -0.4045 1.19
##
## Part.Attractiveness = high, Part.Sex = male:
## Sex sympathyC.trend SE df asymp.LCL asymp.UCL
## male 1.111 0.370 Inf 0.3850 1.84
## female 0.875 0.406 Inf 0.0793 1.67
##
## Part.Attractiveness = low, Part.Sex = male:
## Sex sympathyC.trend SE df asymp.LCL asymp.UCL
## male 1.166 0.370 Inf 0.4403 1.89
## female 0.208 0.406 Inf -0.5871 1.00
##
## Part.Attractiveness = moderate, Part.Sex = female:
## Sex sympathyC.trend SE df asymp.LCL asymp.UCL
## male 1.570 0.370 Inf 0.8439 2.30
## female 0.413 0.406 Inf -0.3819 1.21
##
## Part.Attractiveness = high, Part.Sex = female:
## Sex sympathyC.trend SE df asymp.LCL asymp.UCL
## male 1.073 0.370 Inf 0.3467 1.80
## female 0.414 0.406 Inf -0.3809 1.21
##
## Part.Attractiveness = low, Part.Sex = female:
## Sex sympathyC.trend SE df asymp.LCL asymp.UCL
## male 1.533 0.370 Inf 0.8070 2.26
## female 0.752 0.406 Inf -0.0436 1.55
##
## Degrees-of-freedom method: asymptotic
## Confidence level used: 0.95
##
## $contrasts
## Part.Attractiveness = moderate, Part.Sex = male:
## contrast estimate SE df z.ratio p.value
## male - female 0.841 0.549 Inf 1.531 0.1258
##
## Part.Attractiveness = high, Part.Sex = male:
## contrast estimate SE df z.ratio p.value
## male - female 0.236 0.549 Inf 0.430 0.6671
##
## Part.Attractiveness = low, Part.Sex = male:
## contrast estimate SE df z.ratio p.value
## male - female 0.958 0.549 Inf 1.744 0.0812
##
## Part.Attractiveness = moderate, Part.Sex = female:
## contrast estimate SE df z.ratio p.value
## male - female 1.156 0.549 Inf 2.105 0.0353
##
## Part.Attractiveness = high, Part.Sex = female:
## contrast estimate SE df z.ratio p.value
## male - female 0.658 0.549 Inf 1.198 0.2309
##
## Part.Attractiveness = low, Part.Sex = female:
## contrast estimate SE df z.ratio p.value
## male - female 0.781 0.549 Inf 1.422 0.1551
##
## Degrees-of-freedom method: asymptotic
# Ultimatum Game
## Models
load("UG.Rda")
UG_long$Sex <- relevel(UG_long$Sex, ref = "male")
UG_long$Part.Sex <- relevel(UG_long$Part.Sex, ref = "male")
# baseline model
ModelUG_int<- glmer(UG_Dec~1+(1| ID),data = UG_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
# confirmatory
ModelUG_agree<- glmer(UG_Dec~1+Sex*Part.Attractiveness*Part.Sex*Offer*agreeablenessC+(1| ID),data = UG_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
# without homosexual individuals
ModelUG_agree_sex<- glmer(UG_Dec~1+Sex*Part.Attractiveness*Part.Sex*Offer*agreeablenessC+(1| ID),data = subset(UG_long, sexual_orientation != "homosexual"), family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
# exploratory
ModelUG_fac<- glmer(UG_Dec~1+Sex*Part.Attractiveness*Part.Sex*Offer+(1| ID), data = UG_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelUG_trust<- glmer(UG_Dec~1+Sex*Part.Attractiveness*Part.Sex*Offer*trustC+(1| ID),data = UG_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelUG_mor<- glmer(UG_Dec~1+Sex*Part.Attractiveness*Part.Sex*Offer*moralityC+(1| ID),data = UG_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelUG_alt<- glmer(UG_Dec~1+Sex*Part.Attractiveness*Part.Sex*Offer*altruismC+(1| ID),data = UG_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelUG_coop<- glmer(UG_Dec~1+Sex*Part.Attractiveness*Part.Sex*Offer*cooperationC+(1| ID),data = UG_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelUG_mod<- glmer(UG_Dec~1+Sex*Part.Attractiveness*Part.Sex*Offer*modestyC+(1| ID),data = UG_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelUG_symp<- glmer(UG_Dec~1+Sex*Part.Attractiveness*Part.Sex*Offer*sympathyC+(1| ID),data = UG_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
## Results
### Confirmatory
summary(ModelUG_agree)
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula:
## UG_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * Offer * agreeablenessC +
## (1 | ID)
## Data: UG_long
## Control: glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE)
##
## AIC BIC logLik deviance df.resid
## 6906.8 7442.3 -3380.4 6760.8 11267
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -67.305 -0.258 0.033 0.221 45.441
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 12.05 3.471
## Number of obs: 11340, groups: ID, 210
##
## Fixed effects:
## Estimate
## (Intercept) 1.42335
## Sexfemale 0.97458
## Part.Attractivenesshigh 0.28816
## Part.Attractivenesslow -0.36621
## Part.Sexfemale 0.31873
## Offer1 -2.62175
## Offer5 3.31507
## agreeablenessC 1.86863
## Sexfemale:Part.Attractivenesshigh 0.08234
## Sexfemale:Part.Attractivenesslow 0.20310
## Sexfemale:Part.Sexfemale -0.31257
## Part.Attractivenesshigh:Part.Sexfemale 0.33463
## Part.Attractivenesslow:Part.Sexfemale -0.69181
## Sexfemale:Offer1 -0.58085
## Sexfemale:Offer5 0.93375
## Part.Attractivenesshigh:Offer1 -0.06923
## Part.Attractivenesslow:Offer1 0.14037
## Part.Attractivenesshigh:Offer5 1.02343
## Part.Attractivenesslow:Offer5 -0.13684
## Part.Sexfemale:Offer1 -0.10518
## Part.Sexfemale:Offer5 0.28283
## Sexfemale:agreeablenessC -3.73587
## Part.Attractivenesshigh:agreeablenessC -0.13300
## Part.Attractivenesslow:agreeablenessC -0.56058
## Part.Sexfemale:agreeablenessC 0.16020
## Offer1:agreeablenessC 0.06510
## Offer5:agreeablenessC 1.20851
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -0.67186
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.50409
## Sexfemale:Part.Attractivenesshigh:Offer1 -0.38281
## Sexfemale:Part.Attractivenesslow:Offer1 -0.43305
## Sexfemale:Part.Attractivenesshigh:Offer5 -1.36380
## Sexfemale:Part.Attractivenesslow:Offer5 -0.86177
## Sexfemale:Part.Sexfemale:Offer1 0.02027
## Sexfemale:Part.Sexfemale:Offer5 0.04481
## Part.Attractivenesshigh:Part.Sexfemale:Offer1 -0.13738
## Part.Attractivenesslow:Part.Sexfemale:Offer1 0.22906
## Part.Attractivenesshigh:Part.Sexfemale:Offer5 -0.81329
## Part.Attractivenesslow:Part.Sexfemale:Offer5 0.10259
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 0.90748
## Sexfemale:Part.Attractivenesslow:agreeablenessC 0.77336
## Sexfemale:Part.Sexfemale:agreeablenessC 0.64032
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.12926
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.11018
## Sexfemale:Offer1:agreeablenessC 1.89760
## Sexfemale:Offer5:agreeablenessC -3.33262
## Part.Attractivenesshigh:Offer1:agreeablenessC -0.63437
## Part.Attractivenesslow:Offer1:agreeablenessC -0.80759
## Part.Attractivenesshigh:Offer5:agreeablenessC 1.85173
## Part.Attractivenesslow:Offer5:agreeablenessC 0.16589
## Part.Sexfemale:Offer1:agreeablenessC -0.51538
## Part.Sexfemale:Offer5:agreeablenessC -0.42634
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.66760
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1 0.04229
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5 0.39105
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5 -0.25162
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC -0.16607
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC -0.18107
## Sexfemale:Part.Attractivenesshigh:Offer1:agreeablenessC 0.22602
## Sexfemale:Part.Attractivenesslow:Offer1:agreeablenessC 0.99270
## Sexfemale:Part.Attractivenesshigh:Offer5:agreeablenessC 1.07454
## Sexfemale:Part.Attractivenesslow:Offer5:agreeablenessC 1.23723
## Sexfemale:Part.Sexfemale:Offer1:agreeablenessC 0.38475
## Sexfemale:Part.Sexfemale:Offer5:agreeablenessC 0.53125
## Part.Attractivenesshigh:Part.Sexfemale:Offer1:agreeablenessC 0.03044
## Part.Attractivenesslow:Part.Sexfemale:Offer1:agreeablenessC 1.57640
## Part.Attractivenesshigh:Part.Sexfemale:Offer5:agreeablenessC -1.70813
## Part.Attractivenesslow:Part.Sexfemale:Offer5:agreeablenessC 0.91180
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1:agreeablenessC -0.08235
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1:agreeablenessC -1.07588
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5:agreeablenessC -0.68267
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5:agreeablenessC -1.54634
## Std. Error
## (Intercept) 0.44265
## Sexfemale 0.63326
## Part.Attractivenesshigh 0.27574
## Part.Attractivenesslow 0.27202
## Part.Sexfemale 0.27654
## Offer1 0.30955
## Offer5 0.37491
## agreeablenessC 0.90248
## Sexfemale:Part.Attractivenesshigh 0.40950
## Sexfemale:Part.Attractivenesslow 0.40298
## Sexfemale:Part.Sexfemale 0.40695
## Part.Attractivenesshigh:Part.Sexfemale 0.39517
## Part.Attractivenesslow:Part.Sexfemale 0.38620
## Sexfemale:Offer1 0.44811
## Sexfemale:Offer5 0.69169
## Part.Attractivenesshigh:Offer1 0.42596
## Part.Attractivenesslow:Offer1 0.43532
## Part.Attractivenesshigh:Offer5 0.63093
## Part.Attractivenesslow:Offer5 0.48534
## Part.Sexfemale:Offer1 0.42583
## Part.Sexfemale:Offer5 0.55260
## Sexfemale:agreeablenessC 1.45322
## Part.Attractivenesshigh:agreeablenessC 0.52751
## Part.Attractivenesslow:agreeablenessC 0.52704
## Part.Sexfemale:agreeablenessC 0.52728
## Offer1:agreeablenessC 0.66923
## Offer5:agreeablenessC 0.67988
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.57969
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.56880
## Sexfemale:Part.Attractivenesshigh:Offer1 0.61632
## Sexfemale:Part.Attractivenesslow:Offer1 0.62841
## Sexfemale:Part.Attractivenesshigh:Offer5 0.97917
## Sexfemale:Part.Attractivenesslow:Offer5 0.84281
## Sexfemale:Part.Sexfemale:Offer1 0.61530
## Sexfemale:Part.Sexfemale:Offer5 1.00996
## Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.59746
## Part.Attractivenesslow:Part.Sexfemale:Offer1 0.61654
## Part.Attractivenesshigh:Part.Sexfemale:Offer5 0.92444
## Part.Attractivenesslow:Part.Sexfemale:Offer5 0.72047
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 0.90732
## Sexfemale:Part.Attractivenesslow:agreeablenessC 0.89861
## Sexfemale:Part.Sexfemale:agreeablenessC 0.90046
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.75030
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.74872
## Sexfemale:Offer1:agreeablenessC 1.02716
## Sexfemale:Offer5:agreeablenessC 1.38813
## Part.Attractivenesshigh:Offer1:agreeablenessC 0.88961
## Part.Attractivenesslow:Offer1:agreeablenessC 0.89782
## Part.Attractivenesshigh:Offer5:agreeablenessC 1.06869
## Part.Attractivenesslow:Offer5:agreeablenessC 0.90216
## Part.Sexfemale:Offer1:agreeablenessC 0.90128
## Part.Sexfemale:Offer5:agreeablenessC 1.02052
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.86866
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1 0.89366
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5 1.41695
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5 1.23345
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 1.28136
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 1.26807
## Sexfemale:Part.Attractivenesshigh:Offer1:agreeablenessC 1.39304
## Sexfemale:Part.Attractivenesslow:Offer1:agreeablenessC 1.41370
## Sexfemale:Part.Attractivenesshigh:Offer5:agreeablenessC 2.02660
## Sexfemale:Part.Attractivenesslow:Offer5:agreeablenessC 1.74199
## Sexfemale:Part.Sexfemale:Offer1:agreeablenessC 1.39685
## Sexfemale:Part.Sexfemale:Offer5:agreeablenessC 2.08088
## Part.Attractivenesshigh:Part.Sexfemale:Offer1:agreeablenessC 1.22294
## Part.Attractivenesslow:Part.Sexfemale:Offer1:agreeablenessC 1.30456
## Part.Attractivenesshigh:Part.Sexfemale:Offer5:agreeablenessC 1.64958
## Part.Attractivenesslow:Part.Sexfemale:Offer5:agreeablenessC 1.33540
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1:agreeablenessC 1.94462
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1:agreeablenessC 2.02256
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5:agreeablenessC 2.93713
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5:agreeablenessC 2.57197
## z value
## (Intercept) 3.216
## Sexfemale 1.539
## Part.Attractivenesshigh 1.045
## Part.Attractivenesslow -1.346
## Part.Sexfemale 1.153
## Offer1 -8.470
## Offer5 8.842
## agreeablenessC 2.071
## Sexfemale:Part.Attractivenesshigh 0.201
## Sexfemale:Part.Attractivenesslow 0.504
## Sexfemale:Part.Sexfemale -0.768
## Part.Attractivenesshigh:Part.Sexfemale 0.847
## Part.Attractivenesslow:Part.Sexfemale -1.791
## Sexfemale:Offer1 -1.296
## Sexfemale:Offer5 1.350
## Part.Attractivenesshigh:Offer1 -0.163
## Part.Attractivenesslow:Offer1 0.322
## Part.Attractivenesshigh:Offer5 1.622
## Part.Attractivenesslow:Offer5 -0.282
## Part.Sexfemale:Offer1 -0.247
## Part.Sexfemale:Offer5 0.512
## Sexfemale:agreeablenessC -2.571
## Part.Attractivenesshigh:agreeablenessC -0.252
## Part.Attractivenesslow:agreeablenessC -1.064
## Part.Sexfemale:agreeablenessC 0.304
## Offer1:agreeablenessC 0.097
## Offer5:agreeablenessC 1.778
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -1.159
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.886
## Sexfemale:Part.Attractivenesshigh:Offer1 -0.621
## Sexfemale:Part.Attractivenesslow:Offer1 -0.689
## Sexfemale:Part.Attractivenesshigh:Offer5 -1.393
## Sexfemale:Part.Attractivenesslow:Offer5 -1.022
## Sexfemale:Part.Sexfemale:Offer1 0.033
## Sexfemale:Part.Sexfemale:Offer5 0.044
## Part.Attractivenesshigh:Part.Sexfemale:Offer1 -0.230
## Part.Attractivenesslow:Part.Sexfemale:Offer1 0.372
## Part.Attractivenesshigh:Part.Sexfemale:Offer5 -0.880
## Part.Attractivenesslow:Part.Sexfemale:Offer5 0.142
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 1.000
## Sexfemale:Part.Attractivenesslow:agreeablenessC 0.861
## Sexfemale:Part.Sexfemale:agreeablenessC 0.711
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.172
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.147
## Sexfemale:Offer1:agreeablenessC 1.847
## Sexfemale:Offer5:agreeablenessC -2.401
## Part.Attractivenesshigh:Offer1:agreeablenessC -0.713
## Part.Attractivenesslow:Offer1:agreeablenessC -0.900
## Part.Attractivenesshigh:Offer5:agreeablenessC 1.733
## Part.Attractivenesslow:Offer5:agreeablenessC 0.184
## Part.Sexfemale:Offer1:agreeablenessC -0.572
## Part.Sexfemale:Offer5:agreeablenessC -0.418
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.769
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1 0.047
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5 0.276
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5 -0.204
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC -0.130
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC -0.143
## Sexfemale:Part.Attractivenesshigh:Offer1:agreeablenessC 0.162
## Sexfemale:Part.Attractivenesslow:Offer1:agreeablenessC 0.702
## Sexfemale:Part.Attractivenesshigh:Offer5:agreeablenessC 0.530
## Sexfemale:Part.Attractivenesslow:Offer5:agreeablenessC 0.710
## Sexfemale:Part.Sexfemale:Offer1:agreeablenessC 0.275
## Sexfemale:Part.Sexfemale:Offer5:agreeablenessC 0.255
## Part.Attractivenesshigh:Part.Sexfemale:Offer1:agreeablenessC 0.025
## Part.Attractivenesslow:Part.Sexfemale:Offer1:agreeablenessC 1.208
## Part.Attractivenesshigh:Part.Sexfemale:Offer5:agreeablenessC -1.035
## Part.Attractivenesslow:Part.Sexfemale:Offer5:agreeablenessC 0.683
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1:agreeablenessC -0.042
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1:agreeablenessC -0.532
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5:agreeablenessC -0.232
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5:agreeablenessC -0.601
## Pr(>|z|)
## (Intercept) 0.0013
## Sexfemale 0.1238
## Part.Attractivenesshigh 0.2960
## Part.Attractivenesslow 0.1782
## Part.Sexfemale 0.2491
## Offer1 <2e-16
## Offer5 <2e-16
## agreeablenessC 0.0384
## Sexfemale:Part.Attractivenesshigh 0.8406
## Sexfemale:Part.Attractivenesslow 0.6143
## Sexfemale:Part.Sexfemale 0.4424
## Part.Attractivenesshigh:Part.Sexfemale 0.3971
## Part.Attractivenesslow:Part.Sexfemale 0.0732
## Sexfemale:Offer1 0.1949
## Sexfemale:Offer5 0.1770
## Part.Attractivenesshigh:Offer1 0.8709
## Part.Attractivenesslow:Offer1 0.7471
## Part.Attractivenesshigh:Offer5 0.1048
## Part.Attractivenesslow:Offer5 0.7780
## Part.Sexfemale:Offer1 0.8049
## Part.Sexfemale:Offer5 0.6088
## Sexfemale:agreeablenessC 0.0101
## Part.Attractivenesshigh:agreeablenessC 0.8009
## Part.Attractivenesslow:agreeablenessC 0.2875
## Part.Sexfemale:agreeablenessC 0.7613
## Offer1:agreeablenessC 0.9225
## Offer5:agreeablenessC 0.0755
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.2465
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.3755
## Sexfemale:Part.Attractivenesshigh:Offer1 0.5345
## Sexfemale:Part.Attractivenesslow:Offer1 0.4907
## Sexfemale:Part.Attractivenesshigh:Offer5 0.1637
## Sexfemale:Part.Attractivenesslow:Offer5 0.3065
## Sexfemale:Part.Sexfemale:Offer1 0.9737
## Sexfemale:Part.Sexfemale:Offer5 0.9646
## Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.8181
## Part.Attractivenesslow:Part.Sexfemale:Offer1 0.7102
## Part.Attractivenesshigh:Part.Sexfemale:Offer5 0.3790
## Part.Attractivenesslow:Part.Sexfemale:Offer5 0.8868
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 0.3172
## Sexfemale:Part.Attractivenesslow:agreeablenessC 0.3894
## Sexfemale:Part.Sexfemale:agreeablenessC 0.4770
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.8632
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.8830
## Sexfemale:Offer1:agreeablenessC 0.0647
## Sexfemale:Offer5:agreeablenessC 0.0164
## Part.Attractivenesshigh:Offer1:agreeablenessC 0.4758
## Part.Attractivenesslow:Offer1:agreeablenessC 0.3684
## Part.Attractivenesshigh:Offer5:agreeablenessC 0.0831
## Part.Attractivenesslow:Offer5:agreeablenessC 0.8541
## Part.Sexfemale:Offer1:agreeablenessC 0.5674
## Part.Sexfemale:Offer5:agreeablenessC 0.6761
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.4422
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1 0.9623
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5 0.7826
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5 0.8384
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.8969
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.8865
## Sexfemale:Part.Attractivenesshigh:Offer1:agreeablenessC 0.8711
## Sexfemale:Part.Attractivenesslow:Offer1:agreeablenessC 0.4826
## Sexfemale:Part.Attractivenesshigh:Offer5:agreeablenessC 0.5960
## Sexfemale:Part.Attractivenesslow:Offer5:agreeablenessC 0.4776
## Sexfemale:Part.Sexfemale:Offer1:agreeablenessC 0.7830
## Sexfemale:Part.Sexfemale:Offer5:agreeablenessC 0.7985
## Part.Attractivenesshigh:Part.Sexfemale:Offer1:agreeablenessC 0.9801
## Part.Attractivenesslow:Part.Sexfemale:Offer1:agreeablenessC 0.2269
## Part.Attractivenesshigh:Part.Sexfemale:Offer5:agreeablenessC 0.3004
## Part.Attractivenesslow:Part.Sexfemale:Offer5:agreeablenessC 0.4947
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1:agreeablenessC 0.9662
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1:agreeablenessC 0.5948
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5:agreeablenessC 0.8162
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5:agreeablenessC 0.5477
##
## (Intercept) **
## Sexfemale
## Part.Attractivenesshigh
## Part.Attractivenesslow
## Part.Sexfemale
## Offer1 ***
## Offer5 ***
## agreeablenessC *
## Sexfemale:Part.Attractivenesshigh
## Sexfemale:Part.Attractivenesslow
## Sexfemale:Part.Sexfemale
## Part.Attractivenesshigh:Part.Sexfemale
## Part.Attractivenesslow:Part.Sexfemale .
## Sexfemale:Offer1
## Sexfemale:Offer5
## Part.Attractivenesshigh:Offer1
## Part.Attractivenesslow:Offer1
## Part.Attractivenesshigh:Offer5
## Part.Attractivenesslow:Offer5
## Part.Sexfemale:Offer1
## Part.Sexfemale:Offer5
## Sexfemale:agreeablenessC *
## Part.Attractivenesshigh:agreeablenessC
## Part.Attractivenesslow:agreeablenessC
## Part.Sexfemale:agreeablenessC
## Offer1:agreeablenessC
## Offer5:agreeablenessC .
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale
## Sexfemale:Part.Attractivenesshigh:Offer1
## Sexfemale:Part.Attractivenesslow:Offer1
## Sexfemale:Part.Attractivenesshigh:Offer5
## Sexfemale:Part.Attractivenesslow:Offer5
## Sexfemale:Part.Sexfemale:Offer1
## Sexfemale:Part.Sexfemale:Offer5
## Part.Attractivenesshigh:Part.Sexfemale:Offer1
## Part.Attractivenesslow:Part.Sexfemale:Offer1
## Part.Attractivenesshigh:Part.Sexfemale:Offer5
## Part.Attractivenesslow:Part.Sexfemale:Offer5
## Sexfemale:Part.Attractivenesshigh:agreeablenessC
## Sexfemale:Part.Attractivenesslow:agreeablenessC
## Sexfemale:Part.Sexfemale:agreeablenessC
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC
## Sexfemale:Offer1:agreeablenessC .
## Sexfemale:Offer5:agreeablenessC *
## Part.Attractivenesshigh:Offer1:agreeablenessC
## Part.Attractivenesslow:Offer1:agreeablenessC
## Part.Attractivenesshigh:Offer5:agreeablenessC .
## Part.Attractivenesslow:Offer5:agreeablenessC
## Part.Sexfemale:Offer1:agreeablenessC
## Part.Sexfemale:Offer5:agreeablenessC
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC
## Sexfemale:Part.Attractivenesshigh:Offer1:agreeablenessC
## Sexfemale:Part.Attractivenesslow:Offer1:agreeablenessC
## Sexfemale:Part.Attractivenesshigh:Offer5:agreeablenessC
## Sexfemale:Part.Attractivenesslow:Offer5:agreeablenessC
## Sexfemale:Part.Sexfemale:Offer1:agreeablenessC
## Sexfemale:Part.Sexfemale:Offer5:agreeablenessC
## Part.Attractivenesshigh:Part.Sexfemale:Offer1:agreeablenessC
## Part.Attractivenesslow:Part.Sexfemale:Offer1:agreeablenessC
## Part.Attractivenesshigh:Part.Sexfemale:Offer5:agreeablenessC
## Part.Attractivenesslow:Part.Sexfemale:Offer5:agreeablenessC
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1:agreeablenessC
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1:agreeablenessC
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5:agreeablenessC
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5:agreeablenessC
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation matrix not shown by default, as p = 72 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
car::Anova(ModelUG_agree, type=3)#Type 3 because of sig. interaction effects.
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: UG_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 10.3397 1 0.001302
## Sex 2.3685 1 0.123809
## Part.Attractiveness 5.7289 2 0.057014
## Part.Sex 1.3284 1 0.249087
## Offer 212.7134 2 < 2.2e-16
## agreeablenessC 4.2872 1 0.038400
## Sex:Part.Attractiveness 0.2572 2 0.879321
## Sex:Part.Sex 0.5900 1 0.442431
## Part.Attractiveness:Part.Sex 7.2279 2 0.026945
## Sex:Offer 4.6152 2 0.099499
## Part.Attractiveness:Offer 4.8420 4 0.303891
## Part.Sex:Offer 0.4528 2 0.797384
## Sex:agreeablenessC 6.6088 1 0.010148
## Part.Attractiveness:agreeablenessC 1.2329 2 0.539846
## Part.Sex:agreeablenessC 0.0923 1 0.761266
## Offer:agreeablenessC 3.3451 2 0.187767
## Sex:Part.Attractiveness:Part.Sex 4.2130 2 0.121665
## Sex:Part.Attractiveness:Offer 2.2254 4 0.694390
## Sex:Part.Sex:Offer 0.0024 2 0.998777
## Part.Attractiveness:Part.Sex:Offer 1.2874 4 0.863517
## Sex:Part.Attractiveness:agreeablenessC 1.1770 2 0.555154
## Sex:Part.Sex:agreeablenessC 0.5057 1 0.477020
## Part.Attractiveness:Part.Sex:agreeablenessC 0.0348 2 0.982752
## Sex:Offer:agreeablenessC 12.4299 2 0.001999
## Part.Attractiveness:Offer:agreeablenessC 5.1696 4 0.270332
## Part.Sex:Offer:agreeablenessC 0.3931 2 0.821550
## Sex:Part.Attractiveness:Part.Sex:Offer 0.8550 4 0.930925
## Sex:Part.Attractiveness:Part.Sex:agreeablenessC 0.0249 2 0.987607
## Sex:Part.Attractiveness:Offer:agreeablenessC 0.8791 4 0.927533
## Sex:Part.Sex:Offer:agreeablenessC 0.1104 2 0.946296
## Part.Attractiveness:Part.Sex:Offer:agreeablenessC 3.9295 4 0.415633
## Sex:Part.Attractiveness:Part.Sex:Offer:agreeablenessC 0.5635 4 0.967036
##
## (Intercept) **
## Sex
## Part.Attractiveness .
## Part.Sex
## Offer ***
## agreeablenessC *
## Sex:Part.Attractiveness
## Sex:Part.Sex
## Part.Attractiveness:Part.Sex *
## Sex:Offer .
## Part.Attractiveness:Offer
## Part.Sex:Offer
## Sex:agreeablenessC *
## Part.Attractiveness:agreeablenessC
## Part.Sex:agreeablenessC
## Offer:agreeablenessC
## Sex:Part.Attractiveness:Part.Sex
## Sex:Part.Attractiveness:Offer
## Sex:Part.Sex:Offer
## Part.Attractiveness:Part.Sex:Offer
## Sex:Part.Attractiveness:agreeablenessC
## Sex:Part.Sex:agreeablenessC
## Part.Attractiveness:Part.Sex:agreeablenessC
## Sex:Offer:agreeablenessC **
## Part.Attractiveness:Offer:agreeablenessC
## Part.Sex:Offer:agreeablenessC
## Sex:Part.Attractiveness:Part.Sex:Offer
## Sex:Part.Attractiveness:Part.Sex:agreeablenessC
## Sex:Part.Attractiveness:Offer:agreeablenessC
## Sex:Part.Sex:Offer:agreeablenessC
## Part.Attractiveness:Part.Sex:Offer:agreeablenessC
## Sex:Part.Attractiveness:Part.Sex:Offer:agreeablenessC
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
r.squaredGLMM(ModelUG_agree)
## Warning: the null model is correct only if all variables used by the original
## model remain unchanged.
## R2m R2c
## theoretical 0.3340321 0.8571306
## delta 0.3192482 0.8191951
# Offer
emmeans(ModelUG_agree, pairwise~ Offer, adjust = "bonferroni")
## NOTE: Results may be misleading due to involvement in interactions
## $emmeans
## Offer emmean SE df asymp.LCL asymp.UCL
## 3 1.94 0.288 Inf 1.38 2.505
## 1 -1.06 0.289 Inf -1.62 -0.492
## 5 5.69 0.315 Inf 5.07 6.310
##
## Results are averaged over the levels of: Sex, Part.Attractiveness, Part.Sex
## Results are given on the logit (not the response) scale.
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df z.ratio p.value
## Offer3 - Offer1 3.00 0.106 Inf 28.258 <.0001
## Offer3 - Offer5 -3.75 0.153 Inf -24.565 <.0001
## Offer1 - Offer5 -6.75 0.178 Inf -37.880 <.0001
##
## Results are averaged over the levels of: Sex, Part.Attractiveness, Part.Sex
## Results are given on the log odds ratio (not the response) scale.
## P value adjustment: bonferroni method for 3 tests
# Part.Attractiveness*Participant Sex
emms <- emmeans(ModelUG_agree, ~ Sex*Part.Attractiveness)
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Sex_pairwise Part.Attractiveness_pairwise estimate SE df z.ratio p.value
## male - female moderate - high -0.6594 0.261 Inf -2.525 0.0347
## male - female moderate - low -0.0113 0.237 Inf -0.048 1.0000
## male - female high - low 0.6480 0.236 Inf 2.742 0.0183
##
## Results are averaged over the levels of: Part.Sex, Offer
## Results are given on the log odds ratio (not the response) scale.
## P value adjustment: bonferroni method for 3 tests
# Part.Attractiveness*Part.Sex
emms <- emmeans(ModelUG_agree, ~ Part.Attractiveness*Part.Sex)
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness_pairwise Part.Sex_pairwise estimate SE df z.ratio
## moderate - high male - female -0.142 0.260 Inf -0.546
## moderate - low male - female -0.364 0.236 Inf -1.546
## high - low male - female -0.222 0.233 Inf -0.953
## p.value
## 1.0000
## 0.3664
## 1.0000
##
## Results are averaged over the levels of: Sex, Offer
## Results are given on the log odds ratio (not the response) scale.
## P value adjustment: bonferroni method for 3 tests
# Participant Sex*Trait
emtrends(ModelUG_agree, pairwise ~ Sex, var = "agreeablenessC", adjust = "bonferroni")
## NOTE: Results may be misleading due to involvement in interactions
## $emtrends
## Sex agreeablenessC.trend SE df asymp.LCL asymp.UCL
## male 2.134 0.828 Inf 0.511 3.76
## female -0.901 1.025 Inf -2.909 1.11
##
## Results are averaged over the levels of: Part.Attractiveness, Part.Sex, Offer
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df z.ratio p.value
## male - female 3.03 1.32 Inf 2.303 0.0213
##
## Results are averaged over the levels of: Part.Attractiveness, Part.Sex, Offer
# Participant Sex*Offer*Trait
emtrends(ModelUG_agree, pairwise ~ Sex|Offer, var = "agreeablenessC", adjust = "bonferroni")
## NOTE: Results may be misleading due to involvement in interactions
## $emtrends
## Offer = 3:
## Sex agreeablenessC.trend SE df asymp.LCL asymp.UCL
## male 1.757 0.836 Inf 0.119 3.396
## female -1.156 1.036 Inf -3.187 0.875
##
## Offer = 1:
## Sex agreeablenessC.trend SE df asymp.LCL asymp.UCL
## male 1.352 0.843 Inf -0.300 3.004
## female 0.742 1.037 Inf -1.291 2.775
##
## Offer = 5:
## Sex agreeablenessC.trend SE df asymp.LCL asymp.UCL
## male 3.293 0.878 Inf 1.573 5.013
## female -2.289 1.116 Inf -4.476 -0.101
##
## Results are averaged over the levels of: Part.Attractiveness, Part.Sex
## Confidence level used: 0.95
##
## $contrasts
## Offer = 3:
## contrast estimate SE df z.ratio p.value
## male - female 2.91 1.33 Inf 2.188 0.0287
##
## Offer = 1:
## contrast estimate SE df z.ratio p.value
## male - female 0.61 1.34 Inf 0.456 0.6481
##
## Offer = 5:
## contrast estimate SE df z.ratio p.value
## male - female 5.58 1.42 Inf 3.931 0.0001
##
## Results are averaged over the levels of: Part.Attractiveness, Part.Sex
# check if confirmatory results are stable withouth homosexual individuals
car::Anova(ModelUG_agree_sex, type=3)
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: UG_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 8.9338 1 0.002799
## Sex 2.0682 1 0.150396
## Part.Attractiveness 4.4017 2 0.110710
## Part.Sex 0.9414 1 0.331910
## Offer 198.6685 2 < 2.2e-16
## agreeablenessC 5.1606 1 0.023105
## Sex:Part.Attractiveness 0.1520 2 0.926818
## Sex:Part.Sex 0.4359 1 0.509125
## Part.Attractiveness:Part.Sex 4.1796 2 0.123710
## Sex:Offer 3.2794 2 0.194039
## Part.Attractiveness:Offer 6.0322 4 0.196755
## Part.Sex:Offer 0.4527 2 0.797438
## Sex:agreeablenessC 6.9522 1 0.008372
## Part.Attractiveness:agreeablenessC 1.1603 2 0.559810
## Part.Sex:agreeablenessC 0.0778 1 0.780357
## Offer:agreeablenessC 2.8573 2 0.239634
## Sex:Part.Attractiveness:Part.Sex 2.9397 2 0.229962
## Sex:Part.Attractiveness:Offer 3.5276 4 0.473696
## Sex:Part.Sex:Offer 0.0454 2 0.977580
## Part.Attractiveness:Part.Sex:Offer 2.1035 4 0.716723
## Sex:Part.Attractiveness:agreeablenessC 1.7961 2 0.407373
## Sex:Part.Sex:agreeablenessC 0.9474 1 0.330373
## Part.Attractiveness:Part.Sex:agreeablenessC 0.3615 2 0.834661
## Sex:Offer:agreeablenessC 12.6328 2 0.001806
## Part.Attractiveness:Offer:agreeablenessC 7.9866 4 0.092068
## Part.Sex:Offer:agreeablenessC 0.2390 2 0.887368
## Sex:Part.Attractiveness:Part.Sex:Offer 1.0098 4 0.908308
## Sex:Part.Attractiveness:Part.Sex:agreeablenessC 0.1262 2 0.938827
## Sex:Part.Attractiveness:Offer:agreeablenessC 0.8854 4 0.926652
## Sex:Part.Sex:Offer:agreeablenessC 0.1382 2 0.933248
## Part.Attractiveness:Part.Sex:Offer:agreeablenessC 5.5808 4 0.232717
## Sex:Part.Attractiveness:Part.Sex:Offer:agreeablenessC 0.9738 4 0.913749
##
## (Intercept) **
## Sex
## Part.Attractiveness
## Part.Sex
## Offer ***
## agreeablenessC *
## Sex:Part.Attractiveness
## Sex:Part.Sex
## Part.Attractiveness:Part.Sex
## Sex:Offer
## Part.Attractiveness:Offer
## Part.Sex:Offer
## Sex:agreeablenessC **
## Part.Attractiveness:agreeablenessC
## Part.Sex:agreeablenessC
## Offer:agreeablenessC
## Sex:Part.Attractiveness:Part.Sex
## Sex:Part.Attractiveness:Offer
## Sex:Part.Sex:Offer
## Part.Attractiveness:Part.Sex:Offer
## Sex:Part.Attractiveness:agreeablenessC
## Sex:Part.Sex:agreeablenessC
## Part.Attractiveness:Part.Sex:agreeablenessC
## Sex:Offer:agreeablenessC **
## Part.Attractiveness:Offer:agreeablenessC .
## Part.Sex:Offer:agreeablenessC
## Sex:Part.Attractiveness:Part.Sex:Offer
## Sex:Part.Attractiveness:Part.Sex:agreeablenessC
## Sex:Part.Attractiveness:Offer:agreeablenessC
## Sex:Part.Sex:Offer:agreeablenessC
## Part.Attractiveness:Part.Sex:Offer:agreeablenessC
## Sex:Part.Attractiveness:Part.Sex:Offer:agreeablenessC
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
### Exploratory
models3 <- list(ModelUG_int, ModelUG_fac, ModelUG_agree, ModelUG_trust, ModelUG_mor, ModelUG_alt, ModelUG_coop, ModelUG_mod, ModelUG_symp)
model.names3 <- c('ModelUG_int', 'ModelUG_fac', 'ModelUG_agree', 'ModelUG_trust', 'ModelUG_mor', 'ModelUG_alt', 'ModelUG_coop', 'ModelUG_mod', 'ModelUG_symp')
aictab(cand.set = models3, modnames = model.names3, sort = T)
##
## Model selection based on AICc:
##
## K AICc Delta_AICc AICcWt Cum.Wt LL
## ModelUG_coop 73 6892.51 0.00 0.95 0.95 -3372.78
## ModelUG_alt 73 6898.58 6.07 0.05 1.00 -3375.81
## ModelUG_agree 73 6907.75 15.23 0.00 1.00 -3380.39
## ModelUG_symp 73 6911.52 19.01 0.00 1.00 -3382.28
## ModelUG_mod 73 6941.61 49.10 0.00 1.00 -3397.33
## ModelUG_fac 37 6941.94 49.42 0.00 1.00 -3433.84
## ModelUG_mor 73 6957.11 64.60 0.00 1.00 -3405.08
## ModelUG_trust 73 6962.64 70.12 0.00 1.00 -3407.84
## ModelUG_int 2 11868.36 4975.85 0.00 1.00 -5932.18
anova(ModelUG_coop, ModelUG_alt)
## Data: UG_long
## Models:
## ModelUG_coop: UG_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * Offer * cooperationC + (1 | ID)
## ModelUG_alt: UG_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * Offer * altruismC + (1 | ID)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## ModelUG_coop 73 6891.6 7427.1 -3372.8 6745.6
## ModelUG_alt 73 6897.6 7433.2 -3375.8 6751.6 0 0
car::Anova(ModelUG_coop, type=3)
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: UG_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 6.4703 1 0.01097 *
## Sex 3.2329 1 0.07217 .
## Part.Attractiveness 4.9929 2 0.08238 .
## Part.Sex 1.8643 1 0.17213
## Offer 272.3522 2 < 2e-16 ***
## cooperationC 0.2466 1 0.61949
## Sex:Part.Attractiveness 0.4312 2 0.80606
## Sex:Part.Sex 0.2659 1 0.60607
## Part.Attractiveness:Part.Sex 9.6641 2 0.00797 **
## Sex:Offer 5.0090 2 0.08172 .
## Part.Attractiveness:Offer 2.6401 4 0.61974
## Part.Sex:Offer 1.0687 2 0.58606
## Sex:cooperationC 0.8366 1 0.36038
## Part.Attractiveness:cooperationC 0.8672 2 0.64818
## Part.Sex:cooperationC 0.7691 1 0.38049
## Offer:cooperationC 5.8025 2 0.05496 .
## Sex:Part.Attractiveness:Part.Sex 6.5089 2 0.03860 *
## Sex:Part.Attractiveness:Offer 1.3669 4 0.84993
## Sex:Part.Sex:Offer 0.0882 2 0.95685
## Part.Attractiveness:Part.Sex:Offer 0.4367 4 0.97937
## Sex:Part.Attractiveness:cooperationC 3.1529 2 0.20671
## Sex:Part.Sex:cooperationC 0.0053 1 0.94189
## Part.Attractiveness:Part.Sex:cooperationC 0.3846 2 0.82507
## Sex:Offer:cooperationC 6.0489 2 0.04858 *
## Part.Attractiveness:Offer:cooperationC 2.5679 4 0.63252
## Part.Sex:Offer:cooperationC 0.7141 2 0.69973
## Sex:Part.Attractiveness:Part.Sex:Offer 1.9432 4 0.74621
## Sex:Part.Attractiveness:Part.Sex:cooperationC 0.1355 2 0.93450
## Sex:Part.Attractiveness:Offer:cooperationC 1.6651 4 0.79706
## Sex:Part.Sex:Offer:cooperationC 0.0502 2 0.97519
## Part.Attractiveness:Part.Sex:Offer:cooperationC 7.5537 4 0.10936
## Sex:Part.Attractiveness:Part.Sex:Offer:cooperationC 3.3305 4 0.50412
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(ModelUG_coop)
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula:
## UG_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * Offer * cooperationC +
## (1 | ID)
## Data: UG_long
## Control: glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE)
##
## AIC BIC logLik deviance df.resid
## 6891.6 7427.1 -3372.8 6745.6 11267
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -66.306 -0.252 0.034 0.236 43.107
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 12.16 3.487
## Number of obs: 11340, groups: ID, 210
##
## Fixed effects:
## Estimate
## (Intercept) 1.02501
## Sexfemale 1.01104
## Part.Attractivenesshigh 0.25928
## Part.Attractivenesslow -0.29236
## Part.Sexfemale 0.33396
## Offer1 -2.47332
## Offer5 3.03792
## cooperationC 0.32428
## Sexfemale:Part.Attractivenesshigh 0.18535
## Sexfemale:Part.Attractivenesslow 0.20790
## Sexfemale:Part.Sexfemale -0.17868
## Part.Attractivenesshigh:Part.Sexfemale 0.35070
## Part.Attractivenesslow:Part.Sexfemale -0.71943
## Sexfemale:Offer1 -0.51702
## Sexfemale:Offer5 0.67323
## Part.Attractivenesshigh:Offer1 0.05648
## Part.Attractivenesslow:Offer1 0.31253
## Part.Attractivenesshigh:Offer5 0.41274
## Part.Attractivenesslow:Offer5 -0.03669
## Part.Sexfemale:Offer1 -0.07511
## Part.Sexfemale:Offer5 0.37904
## Sexfemale:cooperationC -0.86563
## Part.Attractivenesshigh:cooperationC -0.30520
## Part.Attractivenesslow:cooperationC -0.33183
## Part.Sexfemale:cooperationC 0.33828
## Offer1:cooperationC 0.97567
## Offer5:cooperationC 0.87594
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -0.69355
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.56068
## Sexfemale:Part.Attractivenesshigh:Offer1 -0.45425
## Sexfemale:Part.Attractivenesslow:Offer1 -0.43677
## Sexfemale:Part.Attractivenesshigh:Offer5 0.13137
## Sexfemale:Part.Attractivenesslow:Offer5 -0.35604
## Sexfemale:Part.Sexfemale:Offer1 0.03981
## Sexfemale:Part.Sexfemale:Offer5 0.21804
## Part.Attractivenesshigh:Part.Sexfemale:Offer1 -0.24946
## Part.Attractivenesslow:Part.Sexfemale:Offer1 -0.08539
## Part.Attractivenesshigh:Part.Sexfemale:Offer5 -0.35520
## Part.Attractivenesslow:Part.Sexfemale:Offer5 -0.24476
## Sexfemale:Part.Attractivenesshigh:cooperationC 0.97527
## Sexfemale:Part.Attractivenesslow:cooperationC 0.20166
## Sexfemale:Part.Sexfemale:cooperationC -0.04127
## Part.Attractivenesshigh:Part.Sexfemale:cooperationC 0.27261
## Part.Attractivenesslow:Part.Sexfemale:cooperationC -0.04672
## Sexfemale:Offer1:cooperationC 0.56807
## Sexfemale:Offer5:cooperationC -1.49629
## Part.Attractivenesshigh:Offer1:cooperationC -0.12283
## Part.Attractivenesslow:Offer1:cooperationC 0.01958
## Part.Attractivenesshigh:Offer5:cooperationC 0.90158
## Part.Attractivenesslow:Offer5:cooperationC 0.36954
## Part.Sexfemale:Offer1:cooperationC -0.53655
## Part.Sexfemale:Offer5:cooperationC -0.32930
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.65650
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1 0.36119
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5 -0.82231
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5 -0.09987
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:cooperationC -0.28052
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:cooperationC -0.22065
## Sexfemale:Part.Attractivenesshigh:Offer1:cooperationC -0.75530
## Sexfemale:Part.Attractivenesslow:Offer1:cooperationC -0.81777
## Sexfemale:Part.Attractivenesshigh:Offer5:cooperationC -1.26743
## Sexfemale:Part.Attractivenesslow:Offer5:cooperationC -0.56962
## Sexfemale:Part.Sexfemale:Offer1:cooperationC 0.04646
## Sexfemale:Part.Sexfemale:Offer5:cooperationC -0.22677
## Part.Attractivenesshigh:Part.Sexfemale:Offer1:cooperationC -0.63407
## Part.Attractivenesslow:Part.Sexfemale:Offer1:cooperationC 1.77185
## Part.Attractivenesshigh:Part.Sexfemale:Offer5:cooperationC -1.48153
## Part.Attractivenesslow:Part.Sexfemale:Offer5:cooperationC 0.16656
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1:cooperationC 1.15984
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1:cooperationC -0.90770
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5:cooperationC 1.94524
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5:cooperationC -0.14118
## Std. Error
## (Intercept) 0.40296
## Sexfemale 0.56230
## Part.Attractivenesshigh 0.24537
## Part.Attractivenesslow 0.24668
## Part.Sexfemale 0.24459
## Offer1 0.28827
## Offer5 0.29103
## cooperationC 0.65304
## Sexfemale:Part.Attractivenesshigh 0.34846
## Sexfemale:Part.Attractivenesslow 0.34762
## Sexfemale:Part.Sexfemale 0.34649
## Part.Attractivenesshigh:Part.Sexfemale 0.34525
## Part.Attractivenesslow:Part.Sexfemale 0.34957
## Sexfemale:Offer1 0.40563
## Sexfemale:Offer5 0.47970
## Part.Attractivenesshigh:Offer1 0.39256
## Part.Attractivenesslow:Offer1 0.39956
## Part.Attractivenesshigh:Offer5 0.43363
## Part.Attractivenesslow:Offer5 0.39080
## Part.Sexfemale:Offer1 0.39319
## Part.Sexfemale:Offer5 0.42948
## Sexfemale:cooperationC 0.94641
## Part.Attractivenesshigh:cooperationC 0.39741
## Part.Attractivenesslow:cooperationC 0.39819
## Part.Sexfemale:cooperationC 0.38573
## Offer1:cooperationC 0.49922
## Offer5:cooperationC 0.44461
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.48966
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.49218
## Sexfemale:Part.Attractivenesshigh:Offer1 0.55435
## Sexfemale:Part.Attractivenesslow:Offer1 0.55957
## Sexfemale:Part.Attractivenesshigh:Offer5 0.74550
## Sexfemale:Part.Attractivenesslow:Offer5 0.63166
## Sexfemale:Part.Sexfemale:Offer1 0.55270
## Sexfemale:Part.Sexfemale:Offer5 0.73520
## Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.54531
## Part.Attractivenesslow:Part.Sexfemale:Offer1 0.57658
## Part.Attractivenesshigh:Part.Sexfemale:Offer5 0.65579
## Part.Attractivenesslow:Part.Sexfemale:Offer5 0.57275
## Sexfemale:Part.Attractivenesshigh:cooperationC 0.57729
## Sexfemale:Part.Attractivenesslow:cooperationC 0.57523
## Sexfemale:Part.Sexfemale:cooperationC 0.56614
## Part.Attractivenesshigh:Part.Sexfemale:cooperationC 0.54863
## Part.Attractivenesslow:Part.Sexfemale:cooperationC 0.55712
## Sexfemale:Offer1:cooperationC 0.68927
## Sexfemale:Offer5:cooperationC 0.75704
## Part.Attractivenesshigh:Offer1:cooperationC 0.65666
## Part.Attractivenesslow:Offer1:cooperationC 0.67416
## Part.Attractivenesshigh:Offer5:cooperationC 0.64915
## Part.Attractivenesslow:Offer5:cooperationC 0.60718
## Part.Sexfemale:Offer1:cooperationC 0.66130
## Part.Sexfemale:Offer5:cooperationC 0.66079
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.77249
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1 0.79525
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5 1.07751
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5 0.96537
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:cooperationC 0.80282
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:cooperationC 0.80903
## Sexfemale:Part.Attractivenesshigh:Offer1:cooperationC 0.93097
## Sexfemale:Part.Attractivenesslow:Offer1:cooperationC 0.95130
## Sexfemale:Part.Attractivenesshigh:Offer5:cooperationC 1.20664
## Sexfemale:Part.Attractivenesslow:Offer5:cooperationC 1.00476
## Sexfemale:Part.Sexfemale:Offer1:cooperationC 0.92996
## Sexfemale:Part.Sexfemale:Offer5:cooperationC 1.16846
## Part.Attractivenesshigh:Part.Sexfemale:Offer1:cooperationC 0.88724
## Part.Attractivenesslow:Part.Sexfemale:Offer1:cooperationC 1.03613
## Part.Attractivenesshigh:Part.Sexfemale:Offer5:cooperationC 1.02744
## Part.Attractivenesslow:Part.Sexfemale:Offer5:cooperationC 0.88346
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1:cooperationC 1.27885
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1:cooperationC 1.39428
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5:cooperationC 1.74827
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5:cooperationC 1.52495
## z value
## (Intercept) 2.544
## Sexfemale 1.798
## Part.Attractivenesshigh 1.057
## Part.Attractivenesslow -1.185
## Part.Sexfemale 1.365
## Offer1 -8.580
## Offer5 10.439
## cooperationC 0.497
## Sexfemale:Part.Attractivenesshigh 0.532
## Sexfemale:Part.Attractivenesslow 0.598
## Sexfemale:Part.Sexfemale -0.516
## Part.Attractivenesshigh:Part.Sexfemale 1.016
## Part.Attractivenesslow:Part.Sexfemale -2.058
## Sexfemale:Offer1 -1.275
## Sexfemale:Offer5 1.403
## Part.Attractivenesshigh:Offer1 0.144
## Part.Attractivenesslow:Offer1 0.782
## Part.Attractivenesshigh:Offer5 0.952
## Part.Attractivenesslow:Offer5 -0.094
## Part.Sexfemale:Offer1 -0.191
## Part.Sexfemale:Offer5 0.883
## Sexfemale:cooperationC -0.915
## Part.Attractivenesshigh:cooperationC -0.768
## Part.Attractivenesslow:cooperationC -0.833
## Part.Sexfemale:cooperationC 0.877
## Offer1:cooperationC 1.954
## Offer5:cooperationC 1.970
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -1.416
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 1.139
## Sexfemale:Part.Attractivenesshigh:Offer1 -0.819
## Sexfemale:Part.Attractivenesslow:Offer1 -0.781
## Sexfemale:Part.Attractivenesshigh:Offer5 0.176
## Sexfemale:Part.Attractivenesslow:Offer5 -0.564
## Sexfemale:Part.Sexfemale:Offer1 0.072
## Sexfemale:Part.Sexfemale:Offer5 0.297
## Part.Attractivenesshigh:Part.Sexfemale:Offer1 -0.457
## Part.Attractivenesslow:Part.Sexfemale:Offer1 -0.148
## Part.Attractivenesshigh:Part.Sexfemale:Offer5 -0.542
## Part.Attractivenesslow:Part.Sexfemale:Offer5 -0.427
## Sexfemale:Part.Attractivenesshigh:cooperationC 1.689
## Sexfemale:Part.Attractivenesslow:cooperationC 0.351
## Sexfemale:Part.Sexfemale:cooperationC -0.073
## Part.Attractivenesshigh:Part.Sexfemale:cooperationC 0.497
## Part.Attractivenesslow:Part.Sexfemale:cooperationC -0.084
## Sexfemale:Offer1:cooperationC 0.824
## Sexfemale:Offer5:cooperationC -1.976
## Part.Attractivenesshigh:Offer1:cooperationC -0.187
## Part.Attractivenesslow:Offer1:cooperationC 0.029
## Part.Attractivenesshigh:Offer5:cooperationC 1.389
## Part.Attractivenesslow:Offer5:cooperationC 0.609
## Part.Sexfemale:Offer1:cooperationC -0.811
## Part.Sexfemale:Offer5:cooperationC -0.498
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.850
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1 0.454
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5 -0.763
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5 -0.103
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:cooperationC -0.349
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:cooperationC -0.273
## Sexfemale:Part.Attractivenesshigh:Offer1:cooperationC -0.811
## Sexfemale:Part.Attractivenesslow:Offer1:cooperationC -0.860
## Sexfemale:Part.Attractivenesshigh:Offer5:cooperationC -1.050
## Sexfemale:Part.Attractivenesslow:Offer5:cooperationC -0.567
## Sexfemale:Part.Sexfemale:Offer1:cooperationC 0.050
## Sexfemale:Part.Sexfemale:Offer5:cooperationC -0.194
## Part.Attractivenesshigh:Part.Sexfemale:Offer1:cooperationC -0.715
## Part.Attractivenesslow:Part.Sexfemale:Offer1:cooperationC 1.710
## Part.Attractivenesshigh:Part.Sexfemale:Offer5:cooperationC -1.442
## Part.Attractivenesslow:Part.Sexfemale:Offer5:cooperationC 0.189
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1:cooperationC 0.907
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1:cooperationC -0.651
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5:cooperationC 1.113
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5:cooperationC -0.093
## Pr(>|z|)
## (Intercept) 0.0110
## Sexfemale 0.0722
## Part.Attractivenesshigh 0.2907
## Part.Attractivenesslow 0.2359
## Part.Sexfemale 0.1721
## Offer1 <2e-16
## Offer5 <2e-16
## cooperationC 0.6195
## Sexfemale:Part.Attractivenesshigh 0.5948
## Sexfemale:Part.Attractivenesslow 0.5498
## Sexfemale:Part.Sexfemale 0.6061
## Part.Attractivenesshigh:Part.Sexfemale 0.3097
## Part.Attractivenesslow:Part.Sexfemale 0.0396
## Sexfemale:Offer1 0.2024
## Sexfemale:Offer5 0.1605
## Part.Attractivenesshigh:Offer1 0.8856
## Part.Attractivenesslow:Offer1 0.4341
## Part.Attractivenesshigh:Offer5 0.3412
## Part.Attractivenesslow:Offer5 0.9252
## Part.Sexfemale:Offer1 0.8485
## Part.Sexfemale:Offer5 0.3775
## Sexfemale:cooperationC 0.3604
## Part.Attractivenesshigh:cooperationC 0.4425
## Part.Attractivenesslow:cooperationC 0.4047
## Part.Sexfemale:cooperationC 0.3805
## Offer1:cooperationC 0.0507
## Offer5:cooperationC 0.0488
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.1567
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.2546
## Sexfemale:Part.Attractivenesshigh:Offer1 0.4125
## Sexfemale:Part.Attractivenesslow:Offer1 0.4351
## Sexfemale:Part.Attractivenesshigh:Offer5 0.8601
## Sexfemale:Part.Attractivenesslow:Offer5 0.5730
## Sexfemale:Part.Sexfemale:Offer1 0.9426
## Sexfemale:Part.Sexfemale:Offer5 0.7668
## Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.6473
## Part.Attractivenesslow:Part.Sexfemale:Offer1 0.8823
## Part.Attractivenesshigh:Part.Sexfemale:Offer5 0.5881
## Part.Attractivenesslow:Part.Sexfemale:Offer5 0.6691
## Sexfemale:Part.Attractivenesshigh:cooperationC 0.0911
## Sexfemale:Part.Attractivenesslow:cooperationC 0.7259
## Sexfemale:Part.Sexfemale:cooperationC 0.9419
## Part.Attractivenesshigh:Part.Sexfemale:cooperationC 0.6193
## Part.Attractivenesslow:Part.Sexfemale:cooperationC 0.9332
## Sexfemale:Offer1:cooperationC 0.4098
## Sexfemale:Offer5:cooperationC 0.0481
## Part.Attractivenesshigh:Offer1:cooperationC 0.8516
## Part.Attractivenesslow:Offer1:cooperationC 0.9768
## Part.Attractivenesshigh:Offer5:cooperationC 0.1649
## Part.Attractivenesslow:Offer5:cooperationC 0.5428
## Part.Sexfemale:Offer1:cooperationC 0.4172
## Part.Sexfemale:Offer5:cooperationC 0.6182
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1 0.3954
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1 0.6497
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5 0.4454
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5 0.9176
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:cooperationC 0.7268
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:cooperationC 0.7851
## Sexfemale:Part.Attractivenesshigh:Offer1:cooperationC 0.4172
## Sexfemale:Part.Attractivenesslow:Offer1:cooperationC 0.3900
## Sexfemale:Part.Attractivenesshigh:Offer5:cooperationC 0.2935
## Sexfemale:Part.Attractivenesslow:Offer5:cooperationC 0.5708
## Sexfemale:Part.Sexfemale:Offer1:cooperationC 0.9602
## Sexfemale:Part.Sexfemale:Offer5:cooperationC 0.8461
## Part.Attractivenesshigh:Part.Sexfemale:Offer1:cooperationC 0.4748
## Part.Attractivenesslow:Part.Sexfemale:Offer1:cooperationC 0.0873
## Part.Attractivenesshigh:Part.Sexfemale:Offer5:cooperationC 0.1493
## Part.Attractivenesslow:Part.Sexfemale:Offer5:cooperationC 0.8505
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1:cooperationC 0.3644
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1:cooperationC 0.5150
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5:cooperationC 0.2659
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5:cooperationC 0.9262
##
## (Intercept) *
## Sexfemale .
## Part.Attractivenesshigh
## Part.Attractivenesslow
## Part.Sexfemale
## Offer1 ***
## Offer5 ***
## cooperationC
## Sexfemale:Part.Attractivenesshigh
## Sexfemale:Part.Attractivenesslow
## Sexfemale:Part.Sexfemale
## Part.Attractivenesshigh:Part.Sexfemale
## Part.Attractivenesslow:Part.Sexfemale *
## Sexfemale:Offer1
## Sexfemale:Offer5
## Part.Attractivenesshigh:Offer1
## Part.Attractivenesslow:Offer1
## Part.Attractivenesshigh:Offer5
## Part.Attractivenesslow:Offer5
## Part.Sexfemale:Offer1
## Part.Sexfemale:Offer5
## Sexfemale:cooperationC
## Part.Attractivenesshigh:cooperationC
## Part.Attractivenesslow:cooperationC
## Part.Sexfemale:cooperationC
## Offer1:cooperationC .
## Offer5:cooperationC *
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale
## Sexfemale:Part.Attractivenesshigh:Offer1
## Sexfemale:Part.Attractivenesslow:Offer1
## Sexfemale:Part.Attractivenesshigh:Offer5
## Sexfemale:Part.Attractivenesslow:Offer5
## Sexfemale:Part.Sexfemale:Offer1
## Sexfemale:Part.Sexfemale:Offer5
## Part.Attractivenesshigh:Part.Sexfemale:Offer1
## Part.Attractivenesslow:Part.Sexfemale:Offer1
## Part.Attractivenesshigh:Part.Sexfemale:Offer5
## Part.Attractivenesslow:Part.Sexfemale:Offer5
## Sexfemale:Part.Attractivenesshigh:cooperationC .
## Sexfemale:Part.Attractivenesslow:cooperationC
## Sexfemale:Part.Sexfemale:cooperationC
## Part.Attractivenesshigh:Part.Sexfemale:cooperationC
## Part.Attractivenesslow:Part.Sexfemale:cooperationC
## Sexfemale:Offer1:cooperationC
## Sexfemale:Offer5:cooperationC *
## Part.Attractivenesshigh:Offer1:cooperationC
## Part.Attractivenesslow:Offer1:cooperationC
## Part.Attractivenesshigh:Offer5:cooperationC
## Part.Attractivenesslow:Offer5:cooperationC
## Part.Sexfemale:Offer1:cooperationC
## Part.Sexfemale:Offer5:cooperationC
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:cooperationC
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:cooperationC
## Sexfemale:Part.Attractivenesshigh:Offer1:cooperationC
## Sexfemale:Part.Attractivenesslow:Offer1:cooperationC
## Sexfemale:Part.Attractivenesshigh:Offer5:cooperationC
## Sexfemale:Part.Attractivenesslow:Offer5:cooperationC
## Sexfemale:Part.Sexfemale:Offer1:cooperationC
## Sexfemale:Part.Sexfemale:Offer5:cooperationC
## Part.Attractivenesshigh:Part.Sexfemale:Offer1:cooperationC
## Part.Attractivenesslow:Part.Sexfemale:Offer1:cooperationC .
## Part.Attractivenesshigh:Part.Sexfemale:Offer5:cooperationC
## Part.Attractivenesslow:Part.Sexfemale:Offer5:cooperationC
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer1:cooperationC
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer1:cooperationC
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:Offer5:cooperationC
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:Offer5:cooperationC
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation matrix not shown by default, as p = 72 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
# Participant Sex*Offer*Trait
emtrends(ModelUG_coop, pairwise ~ Sex|Offer, var = "cooperationC", adjust = "bonferroni")
## NOTE: Results may be misleading due to involvement in interactions
## $emtrends
## Offer = 3:
## Sex cooperationC.trend SE df asymp.LCL asymp.UCL
## male 0.319 0.602 Inf -0.8611 1.4985
## female -0.259 0.630 Inf -1.4944 0.9769
##
## Offer = 1:
## Sex cooperationC.trend SE df asymp.LCL asymp.UCL
## male 1.181 0.612 Inf -0.0186 2.3812
## female 0.713 0.635 Inf -0.5315 1.9572
##
## Offer = 5:
## Sex cooperationC.trend SE df asymp.LCL asymp.UCL
## male 1.235 0.618 Inf 0.0240 2.4451
## female -1.264 0.679 Inf -2.5950 0.0665
##
## Results are averaged over the levels of: Part.Attractiveness, Part.Sex
## Confidence level used: 0.95
##
## $contrasts
## Offer = 3:
## contrast estimate SE df z.ratio p.value
## male - female 0.577 0.872 Inf 0.663 0.5076
##
## Offer = 1:
## contrast estimate SE df z.ratio p.value
## male - female 0.469 0.882 Inf 0.531 0.5953
##
## Offer = 5:
## contrast estimate SE df z.ratio p.value
## male - female 2.499 0.918 Inf 2.722 0.0065
##
## Results are averaged over the levels of: Part.Attractiveness, Part.Sex
# Participant Sex*Part.Attractiveness*Part.Sex
emms <- emmeans(ModelUG_coop, ~ Part.Attractiveness*Part.Sex|Sex)
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Sex = male:
## Part.Attractiveness_pairwise Part.Sex_pairwise estimate SE df z.ratio
## moderate - high male - female 0.149 0.260 Inf 0.574
## moderate - low male - female -0.829 0.245 Inf -3.390
## high - low male - female -0.979 0.256 Inf -3.820
## p.value
## 1.0000
## 0.0021
## 0.0004
##
## Sex = female:
## Part.Attractiveness_pairwise Part.Sex_pairwise estimate SE df z.ratio
## moderate - high male - female -0.600 0.318 Inf -1.886
## moderate - low male - female -0.182 0.295 Inf -0.616
## high - low male - female 0.418 0.298 Inf 1.403
## p.value
## 0.1779
## 1.0000
## 0.4818
##
## Results are averaged over the levels of: Offer
## Results are given on the log odds ratio (not the response) scale.
## P value adjustment: bonferroni method for 3 tests
# Prisoners Dilemma
load("PD.Rda")
PD_long$Sex <- relevel(PD_long$Sex, ref = "male")
PD_long$Part.Sex <- relevel(PD_long$Part.Sex, ref = "male")
## Models
# baseline
ModelPD_int<- glmer(PD_Dec~1+(1| ID),data = PD_long, family = "binomial")
# confirmatory
ModelPD_agree<- glmer(PD_Dec~1+Sex*Part.Attractiveness*Part.Sex*agreeablenessC+(1| ID),data = PD_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
# without homosexual individuals
ModelPD_agree_sex<- glmer(PD_Dec~1+Sex*Part.Attractiveness*Part.Sex*agreeablenessC+(1| ID),data = subset(PD_long, sexual_orientation != "homosexual"), family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
# exploratory
ModelPD_fac<- glmer(PD_Dec~1+Sex*Part.Attractiveness*Part.Sex+(1| ID), data = PD_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelPD_trust<- glmer(PD_Dec~1+Sex*Part.Attractiveness*Part.Sex*trustC+(1| ID),data = PD_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelPD_mor<- glmer(PD_Dec~1+Sex*Part.Attractiveness*Part.Sex*moralityC+(1| ID), data = PD_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelPD_alt<- glmer(PD_Dec~1+Sex*Part.Attractiveness*Part.Sex*altruismC+(1| ID), data = PD_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelPD_coop<- glmer(PD_Dec~1+Sex*Part.Attractiveness*Part.Sex*cooperationC+(1| ID), data = PD_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelPD_mod<- glmer(PD_Dec~1+Sex*Part.Attractiveness*Part.Sex*modestyC+(1| ID), data = PD_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
ModelPD_symp<- glmer(PD_Dec~1+Sex*Part.Attractiveness*Part.Sex*sympathyC+(1| ID), data = PD_long, family = "binomial", control = glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE))
## Results
### Confirmatory
summary(ModelPD_agree)
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: PD_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * agreeablenessC +
## (1 | ID)
## Data: PD_long
## Control: glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE)
##
## AIC BIC logLik deviance df.resid
## 3685.4 3841.3 -1817.7 3635.4 3755
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.5355 -0.5506 0.1731 0.4980 4.6871
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 4.327 2.08
## Number of obs: 3780, groups: ID, 210
##
## Fixed effects:
## Estimate
## (Intercept) 1.27435
## Sexfemale -0.48238
## Part.Attractivenesshigh 1.03366
## Part.Attractivenesslow -0.60134
## Part.Sexfemale 0.10400
## agreeablenessC 1.52427
## Sexfemale:Part.Attractivenesshigh 0.71133
## Sexfemale:Part.Attractivenesslow 0.24707
## Sexfemale:Part.Sexfemale 1.06416
## Part.Attractivenesshigh:Part.Sexfemale 0.12338
## Part.Attractivenesslow:Part.Sexfemale -0.93464
## Sexfemale:agreeablenessC -0.91123
## Part.Attractivenesshigh:agreeablenessC 0.62245
## Part.Attractivenesslow:agreeablenessC -0.22287
## Part.Sexfemale:agreeablenessC 0.09353
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -1.51533
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale -0.15273
## Sexfemale:Part.Attractivenesshigh:agreeablenessC -0.20988
## Sexfemale:Part.Attractivenesslow:agreeablenessC -1.16360
## Sexfemale:Part.Sexfemale:agreeablenessC -0.33981
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC -0.14825
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.29346
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.85441
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 1.08322
## Std. Error
## (Intercept) 0.29716
## Sexfemale 0.41477
## Part.Attractivenesshigh 0.26620
## Part.Attractivenesslow 0.23519
## Part.Sexfemale 0.23938
## agreeablenessC 0.61390
## Sexfemale:Part.Attractivenesshigh 0.37061
## Sexfemale:Part.Attractivenesslow 0.32837
## Sexfemale:Part.Sexfemale 0.34010
## Part.Attractivenesshigh:Part.Sexfemale 0.38167
## Part.Attractivenesslow:Part.Sexfemale 0.33873
## Sexfemale:agreeablenessC 0.95845
## Part.Attractivenesshigh:agreeablenessC 0.53666
## Part.Attractivenesslow:agreeablenessC 0.48449
## Part.Sexfemale:agreeablenessC 0.49347
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.52796
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.47527
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 0.86636
## Sexfemale:Part.Attractivenesslow:agreeablenessC 0.76079
## Sexfemale:Part.Sexfemale:agreeablenessC 0.78887
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.76840
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.70007
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 1.23600
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 1.10050
## z value
## (Intercept) 4.288
## Sexfemale -1.163
## Part.Attractivenesshigh 3.883
## Part.Attractivenesslow -2.557
## Part.Sexfemale 0.434
## agreeablenessC 2.483
## Sexfemale:Part.Attractivenesshigh 1.919
## Sexfemale:Part.Attractivenesslow 0.752
## Sexfemale:Part.Sexfemale 3.129
## Part.Attractivenesshigh:Part.Sexfemale 0.323
## Part.Attractivenesslow:Part.Sexfemale -2.759
## Sexfemale:agreeablenessC -0.951
## Part.Attractivenesshigh:agreeablenessC 1.160
## Part.Attractivenesslow:agreeablenessC -0.460
## Part.Sexfemale:agreeablenessC 0.190
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -2.870
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale -0.321
## Sexfemale:Part.Attractivenesshigh:agreeablenessC -0.242
## Sexfemale:Part.Attractivenesslow:agreeablenessC -1.529
## Sexfemale:Part.Sexfemale:agreeablenessC -0.431
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC -0.193
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.419
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.691
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.984
## Pr(>|z|)
## (Intercept) 1.8e-05 ***
## Sexfemale 0.244819
## Part.Attractivenesshigh 0.000103 ***
## Part.Attractivenesslow 0.010563 *
## Part.Sexfemale 0.663953
## agreeablenessC 0.013030 *
## Sexfemale:Part.Attractivenesshigh 0.054939 .
## Sexfemale:Part.Attractivenesslow 0.451808
## Sexfemale:Part.Sexfemale 0.001754 **
## Part.Attractivenesshigh:Part.Sexfemale 0.746496
## Part.Attractivenesslow:Part.Sexfemale 0.005794 **
## Sexfemale:agreeablenessC 0.341742
## Part.Attractivenesshigh:agreeablenessC 0.246103
## Part.Attractivenesslow:agreeablenessC 0.645509
## Part.Sexfemale:agreeablenessC 0.849665
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale 0.004103 **
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale 0.747935
## Sexfemale:Part.Attractivenesshigh:agreeablenessC 0.808584
## Sexfemale:Part.Attractivenesslow:agreeablenessC 0.126151
## Sexfemale:Part.Sexfemale:agreeablenessC 0.666650
## Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.847007
## Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.675083
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:agreeablenessC 0.489394
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:agreeablenessC 0.324968
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation matrix not shown by default, as p = 24 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
car::Anova(ModelPD_agree, type=3)#Type 3 because of sig. interaction effects.
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: PD_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 18.3908 1 1.799e-05 ***
## Sex 1.3526 1 0.244819
## Part.Attractiveness 38.0841 2 5.372e-09 ***
## Part.Sex 0.1888 1 0.663953
## agreeablenessC 6.1650 1 0.013030 *
## Sex:Part.Attractiveness 3.6945 2 0.157669
## Sex:Part.Sex 9.7904 1 0.001754 **
## Part.Attractiveness:Part.Sex 10.5871 2 0.005024 **
## Sex:agreeablenessC 0.9039 1 0.341742
## Part.Attractiveness:agreeablenessC 2.5953 2 0.273174
## Part.Sex:agreeablenessC 0.0359 1 0.849665
## Sex:Part.Attractiveness:Part.Sex 9.5197 2 0.008567 **
## Sex:Part.Attractiveness:agreeablenessC 2.5474 2 0.279789
## Sex:Part.Sex:agreeablenessC 0.1855 1 0.666650
## Part.Attractiveness:Part.Sex:agreeablenessC 0.3596 2 0.835417
## Sex:Part.Attractiveness:Part.Sex:agreeablenessC 1.0420 2 0.593916
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
r.squaredGLMM(ModelPD_agree)
## Warning: the null model is correct only if all variables used by the original
## model remain unchanged.
## R2m R2c
## theoretical 0.1421025 0.6294388
## delta 0.1256253 0.5564536
# Part.Attractiveness
emmeans(ModelPD_agree, pairwise~ Part.Attractiveness, adjust = "bonferroni")
## NOTE: Results may be misleading due to involvement in interactions
## $emmeans
## Part.Attractiveness emmean SE df asymp.LCL asymp.UCL
## moderate 1.351 0.192 Inf 0.975 1.727
## high 2.423 0.201 Inf 2.029 2.818
## low 0.368 0.189 Inf -0.002 0.738
##
## Results are averaged over the levels of: Sex, Part.Sex
## Results are given on the logit (not the response) scale.
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df z.ratio p.value
## moderate - high -1.072 0.133 Inf -8.060 <.0001
## moderate - low 0.983 0.120 Inf 8.221 <.0001
## high - low 2.055 0.135 Inf 15.281 <.0001
##
## Results are averaged over the levels of: Sex, Part.Sex
## Results are given on the log odds ratio (not the response) scale.
## P value adjustment: bonferroni method for 3 tests
# Participant Sex*Part.Sex
emms <- emmeans(ModelPD_agree, ~ Part.Sex|Sex)
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Sex = male:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female 0.166 0.150 Inf 1.108 0.2677
##
## Sex = female:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.342 0.143 Inf -2.383 0.0172
##
## Results are averaged over the levels of: Part.Attractiveness
## Results are given on the log odds ratio (not the response) scale.
# Part.Attractiveness*Part.Sex
emms <- emmeans(ModelPD_agree, ~ Part.Sex|Part.Attractiveness)
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness = moderate:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.6361 0.170 Inf -3.741 0.0002
##
## Part.Attractiveness = high:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female -0.0018 0.202 Inf -0.009 0.9929
##
## Part.Attractiveness = low:
## Part.Sex_pairwise estimate SE df z.ratio p.value
## male - female 0.3749 0.166 Inf 2.261 0.0238
##
## Results are averaged over the levels of: Sex
## Results are given on the log odds ratio (not the response) scale.
# Participant Sex*Part.Attractiveness*Part.Sex
emms <- emmeans(ModelPD_agree, ~ Part.Sex*Part.Attractiveness|Sex)
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Sex = male:
## Part.Sex_pairwise Part.Attractiveness_pairwise estimate SE df z.ratio
## male - female moderate - high 0.123 0.382 Inf 0.323
## male - female moderate - low -0.935 0.339 Inf -2.759
## male - female high - low -1.058 0.382 Inf -2.771
## p.value
## 1.0000
## 0.0174
## 0.0168
##
## Sex = female:
## Part.Sex_pairwise Part.Attractiveness_pairwise estimate SE df z.ratio
## male - female moderate - high -1.392 0.365 Inf -3.816
## male - female moderate - low -1.087 0.333 Inf -3.262
## male - female high - low 0.305 0.356 Inf 0.855
## p.value
## 0.0004
## 0.0033
## 1.0000
##
## Results are given on the log odds ratio (not the response) scale.
## P value adjustment: bonferroni method for 3 tests
# check if confirmatory results are stable withouth homosexual individuals
car::Anova(ModelPD_agree_sex, type=3)
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: PD_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 10.2806 1 0.001344 **
## Sex 0.0368 1 0.847842
## Part.Attractiveness 31.5368 2 1.419e-07 ***
## Part.Sex 0.4180 1 0.517924
## agreeablenessC 4.3097 1 0.037896 *
## Sex:Part.Attractiveness 3.1642 2 0.205540
## Sex:Part.Sex 7.9099 1 0.004917 **
## Part.Attractiveness:Part.Sex 9.8938 2 0.007105 **
## Sex:agreeablenessC 0.7434 1 0.388563
## Part.Attractiveness:agreeablenessC 0.8654 2 0.648761
## Part.Sex:agreeablenessC 0.1499 1 0.698603
## Sex:Part.Attractiveness:Part.Sex 6.8975 2 0.031786 *
## Sex:Part.Attractiveness:agreeablenessC 4.0983 2 0.128847
## Sex:Part.Sex:agreeablenessC 0.3427 1 0.558290
## Part.Attractiveness:Part.Sex:agreeablenessC 0.4616 2 0.793904
## Sex:Part.Attractiveness:Part.Sex:agreeablenessC 1.1448 2 0.564163
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
### Exploratory
models4 <- list(ModelPD_int, ModelPD_fac, ModelPD_agree, ModelPD_trust, ModelPD_mor, ModelPD_alt, ModelPD_coop, ModelPD_mod, ModelPD_symp )
model.names4 <- c('ModelPD_int', 'ModelPD_fac', 'ModelPD_agree', 'ModelPD_trust', 'ModelPD_mor', 'ModelPD_alt', 'ModelPD_coop', 'ModelPD_mod', 'ModelPD_symp')
aictab(cand.set = models4, modnames = model.names4, sort = T)
##
## Model selection based on AICc:
##
## K AICc Delta_AICc AICcWt Cum.Wt LL
## ModelPD_trust 25 3679.84 0.00 0.86 0.86 -1814.75
## ModelPD_coop 25 3684.83 4.99 0.07 0.93 -1817.24
## ModelPD_agree 25 3685.73 5.89 0.05 0.97 -1817.69
## ModelPD_symp 25 3688.10 8.26 0.01 0.98 -1818.88
## ModelPD_fac 13 3688.57 8.73 0.01 1.00 -1831.24
## ModelPD_alt 25 3690.20 10.36 0.00 1.00 -1819.93
## ModelPD_mor 25 3700.36 20.53 0.00 1.00 -1825.01
## ModelPD_mod 25 3705.03 25.19 0.00 1.00 -1827.34
## ModelPD_int 2 4101.66 421.82 0.00 1.00 -2048.83
anova(ModelPD_trust, ModelPD_coop)
## Data: PD_long
## Models:
## ModelPD_trust: PD_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * trustC + (1 | ID)
## ModelPD_coop: PD_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * cooperationC + (1 | ID)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## ModelPD_trust 25 3679.5 3835.4 -1814.8 3629.5
## ModelPD_coop 25 3684.5 3840.4 -1817.2 3634.5 0 0
car::Anova(ModelPD_trust, type=3)
## Analysis of Deviance Table (Type III Wald chisquare tests)
##
## Response: PD_Dec
## Chisq Df Pr(>Chisq)
## (Intercept) 14.4928 1 0.0001407 ***
## Sex 0.0638 1 0.8005677
## Part.Attractiveness 38.2098 2 5.045e-09 ***
## Part.Sex 0.0007 1 0.9793804
## trustC 3.7476 1 0.0528836 .
## Sex:Part.Attractiveness 6.5017 2 0.0387421 *
## Sex:Part.Sex 10.5828 1 0.0011415 **
## Part.Attractiveness:Part.Sex 11.5573 2 0.0030928 **
## Sex:trustC 1.6135 1 0.2040052
## Part.Attractiveness:trustC 1.0673 2 0.5864710
## Part.Sex:trustC 0.7007 1 0.4025345
## Sex:Part.Attractiveness:Part.Sex 13.9813 2 0.0009205 ***
## Sex:Part.Attractiveness:trustC 4.8722 2 0.0875034 .
## Sex:Part.Sex:trustC 1.3486 1 0.2455193
## Part.Attractiveness:Part.Sex:trustC 5.2617 2 0.0720179 .
## Sex:Part.Attractiveness:Part.Sex:trustC 3.3457 2 0.1877112
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
r.squaredGLMM(ModelPD_trust)
## Warning: the null model is correct only if all variables used by the original
## model remain unchanged.
## R2m R2c
## theoretical 0.1363389 0.6385624
## delta 0.1208751 0.5661355
summary(ModelPD_trust)
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: PD_Dec ~ 1 + Sex * Part.Attractiveness * Part.Sex * trustC +
## (1 | ID)
## Data: PD_long
## Control: glmerControl(optimizer = "nloptwrap", calc.derivs = FALSE)
##
## AIC BIC logLik deviance df.resid
## 3679.5 3835.4 -1814.7 3629.5 3755
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.6939 -0.5605 0.1774 0.5046 4.8420
##
## Random effects:
## Groups Name Variance Std.Dev.
## ID (Intercept) 4.571 2.138
## Number of obs: 3780, groups: ID, 210
##
## Fixed effects:
## Estimate Std. Error
## (Intercept) 1.109577 0.291461
## Sexfemale -0.101427 0.401513
## Part.Attractivenesshigh 0.807887 0.239910
## Part.Attractivenesslow -0.679423 0.227193
## Part.Sexfemale -0.005866 0.226978
## trustC 0.853380 0.440825
## Sexfemale:Part.Attractivenesshigh 0.808686 0.337627
## Sexfemale:Part.Attractivenesslow 0.094266 0.311014
## Sexfemale:Part.Sexfemale 1.031496 0.317079
## Part.Attractivenesshigh:Part.Sexfemale 0.487398 0.351896
## Part.Attractivenesslow:Part.Sexfemale -0.701616 0.325795
## Sexfemale:trustC -0.806323 0.634789
## Part.Attractivenesshigh:trustC -0.144257 0.374489
## Part.Attractivenesslow:trustC -0.357155 0.347430
## Part.Sexfemale:trustC -0.295594 0.353115
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -1.650140 0.487533
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale -0.065972 0.447272
## Sexfemale:Part.Attractivenesshigh:trustC 1.122041 0.547579
## Sexfemale:Part.Attractivenesslow:trustC 0.079590 0.491444
## Sexfemale:Part.Sexfemale:trustC 0.587759 0.506121
## Part.Attractivenesshigh:Part.Sexfemale:trustC 1.014846 0.535723
## Part.Attractivenesslow:Part.Sexfemale:trustC 1.024723 0.506054
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:trustC -1.256162 0.778991
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:trustC -1.077841 0.712877
## z value Pr(>|z|)
## (Intercept) 3.807 0.000141 ***
## Sexfemale -0.253 0.800568
## Part.Attractivenesshigh 3.367 0.000759 ***
## Part.Attractivenesslow -2.991 0.002785 **
## Part.Sexfemale -0.026 0.979380
## trustC 1.936 0.052884 .
## Sexfemale:Part.Attractivenesshigh 2.395 0.016611 *
## Sexfemale:Part.Attractivenesslow 0.303 0.761818
## Sexfemale:Part.Sexfemale 3.253 0.001141 **
## Part.Attractivenesshigh:Part.Sexfemale 1.385 0.166033
## Part.Attractivenesslow:Part.Sexfemale -2.154 0.031276 *
## Sexfemale:trustC -1.270 0.204005
## Part.Attractivenesshigh:trustC -0.385 0.700081
## Part.Attractivenesslow:trustC -1.028 0.303954
## Part.Sexfemale:trustC -0.837 0.402535
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale -3.385 0.000713 ***
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale -0.147 0.882738
## Sexfemale:Part.Attractivenesshigh:trustC 2.049 0.040453 *
## Sexfemale:Part.Attractivenesslow:trustC 0.162 0.871344
## Sexfemale:Part.Sexfemale:trustC 1.161 0.245519
## Part.Attractivenesshigh:Part.Sexfemale:trustC 1.894 0.058179 .
## Part.Attractivenesslow:Part.Sexfemale:trustC 2.025 0.042875 *
## Sexfemale:Part.Attractivenesshigh:Part.Sexfemale:trustC -1.613 0.106842
## Sexfemale:Part.Attractivenesslow:Part.Sexfemale:trustC -1.512 0.130544
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation matrix not shown by default, as p = 24 > 12.
## Use print(x, correlation=TRUE) or
## vcov(x) if you need it
# Attractiveness
emmeans(ModelPD_trust, pairwise~ Part.Attractiveness, adjust = "bonferroni")
## NOTE: Results may be misleading due to involvement in interactions
## $emmeans
## Part.Attractiveness emmean SE df asymp.LCL asymp.UCL
## moderate 1.314 0.186 Inf 0.949 1.679
## high 2.357 0.194 Inf 1.978 2.737
## low 0.314 0.184 Inf -0.046 0.674
##
## Results are averaged over the levels of: Sex, Part.Sex
## Results are given on the logit (not the response) scale.
## Confidence level used: 0.95
##
## $contrasts
## contrast estimate SE df z.ratio p.value
## moderate - high -1.04 0.123 Inf -8.501 <.0001
## moderate - low 1.00 0.113 Inf 8.861 <.0001
## high - low 2.04 0.125 Inf 16.326 <.0001
##
## Results are averaged over the levels of: Sex, Part.Sex
## Results are given on the log odds ratio (not the response) scale.
## P value adjustment: bonferroni method for 3 tests
# Participant Sex*Part.Attractiveness
emms <- emmeans(ModelPD_trust, ~ Part.Attractiveness*Sex)
## NOTE: Results may be misleading due to involvement in interactions
contrast(emms, interaction = "pairwise", adjust = "bonferroni")
## Part.Attractiveness_pairwise Sex_pairwise estimate SE df z.ratio p.value
## moderate - high male - female -0.0164 0.245 Inf -0.067 1.0000
## moderate - low male - female 0.0613 0.226 Inf 0.272 1.0000
## high - low male - female 0.0777 0.250 Inf 0.310 1.0000
##
## Results are averaged over the levels of: Part.Sex
## Results are given on the log odds ratio (not the response) scale.
## P value adjustment: bonferroni method for 3 tests
*END