Pesquisa Fernanda Fuentes
Danilo A Pereira
29/01/2021
Banco de dados
library(readxl)
library(tidyverse)
# Read dataset
database <- read.csv("C:/Dropbox/Laboratorio/Fernanda Gomes/Baseline.csv")
# See names
colnames(database)## [1] "ID" "Group" "Age"
## [4] "Race" "Education" "Type"
## [7] "carac_abuso" "profilaxia" "q1"
## [10] "q2" "q3" "q4"
## [13] "q5" "q6" "q7"
## [16] "q8" "q9" "q10"
## [19] "q11" "q12" "q13"
## [22] "q14" "q15" "q16"
## [25] "q17" "q18" "q19"
## [28] "q20" "q21" "q22"
## [31] "q23" "q24" "q25"
## [34] "q26" "q27" "q28"
## [37] "Quesi" "CAPS.A" "CAPS.B"
## [40] "CAPS.C" "CAPS.D" "CAPS.E"
## [43] "CAPS.BE" "CAPS.G" "Depersonalization"
## [46] "Derealization" "Dissociation" "Vocabulary"
## [49] "Matrix.Reasoning" "IQ" "A1"
## [52] "A2" "A3" "A4"
## [55] "A5" "B1" "A6"
## [58] "A7" "Recog.A" "Recog.B"
## [61] "erro_fa" "erro_fb" "erro_sa"
## [64] "erro_sb" "int_proativa" "int_retroativa"
## [67] "Intrusion" "Perseverance" "Primacy"
## [70] "Recency" "Total.RAVLT" "Forgetfulness.Rate"
## [73] "n_cat" "n_erro" "perda_set"
## [76] "tempo_c" "Time.CW" "Time.C"
## [79] "acertos_cw" "total_erros_c" "total_erros_cw"
## [82] "cw_c" "Digits.forward" "Digits.backward"
## [85] "total_digitos" "digitos_direto_inverso" "Span.forward"
## [88] "Span.backward" "Corsi.forward" "Corsi.backward"
## [91] "corsi_total" "corsi_direto_inverso" "corsi_span_direto"
## [94] "corsi_span_inverso" "lembra_espontanea" "lembra_dica"
## [97] "nao_lembra" "d2.RB" "d2.RL"
## [100] "d2_ao" "d2_porcentagem_erros" "d2_erro1"
## [103] "d2_erro2" "d2_1_4" "d2_5_1."
## [106] "d2_11_14" "d2_erro_total" "fdt_lei_tempo1"
## [109] "fdt_lei_erro1" "fdt_lei_tempo2" "fdt_lei_erro2"
## [112] "Reading.time" "fdt_lei_erro_total" "fdt_con_tempo1"
## [115] "fdt_con_erro1" "fdt_con_tempo2" "fdt_con_erro2"
## [118] "Count.time" "fdt_con_erro_total" "fdt_esc_tempo1"
## [121] "fdt_esc_erro1" "fdt_esc_tempo2" "fdt_esc_erro2"
## [124] "Choice.time" "fdt_esc_erro_total" "fdt_alt_tempo1"
## [127] "fdt_alt_erro1" "fdt_alt_tempo2" "fdt_alt_erro2"
## [130] "Alternation.time" "fdt_alt_erro_total" "Inhibition"
## [133] "Flexibility"# Select variables
red <- database %>% select(Group, Age, Education, Type, Quesi, Depersonalization:Matrix.Reasoning,
IQ:Recog.B,Intrusion:Forgetfulness.Rate, Time.CW, Time.C, Digits.forward, Digits.backward,
Span.forward:Corsi.backward, d2.RB, d2.RL, Reading.time, Count.time, Choice.time,
Alternation.time, Inhibition, Flexibility, n_cat, n_erro, perda_set, Time.C, Time.CW)
# See variables
red %>% glimpse()## Rows: 45
## Columns: 46
## $ Group <chr> "Case", "Case", "Case", "Case", "Case", "Case", ...
## $ Age <int> 16, 14, 14, 17, 17, 17, 14, 14, 14, 14, 15, 14, ...
## $ Education <int> 11, 10, 8, 12, 12, 12, 10, 10, 9, 8, 11, 9, 11, ...
## $ Type <chr> "Once", "Once", "Once", "Once", "Once", "Once", ...
## $ Quesi <int> 55, 67, 49, 40, 42, 54, 50, 53, 57, 42, 39, 88, ...
## $ Depersonalization <int> 2, 0, 0, 1, 0, 0, 4, 0, 0, 1, 2, 4, 1, 0, 0, 2, ...
## $ Derealization <int> 2, 1, 0, 2, 0, 0, 4, 0, 0, 0, 0, 4, 1, 2, 0, 2, ...
## $ Dissociation <int> 4, 1, 0, 3, 0, 0, 8, 0, 0, 1, 2, 8, 2, 2, 0, 4, ...
## $ Vocabulary <int> 44, 30, 48, 39, 42, 28, 22, 42, 55, 41, 56, 44, ...
## $ Matrix.Reasoning <int> 18, 16, 27, 14, 25, 25, 24, 21, 24, 29, 28, 27, ...
## $ IQ <int> 80, 70, 99, 72, 89, 80, 77, 87, 101, 98, 104, 95...
## $ A1 <int> 7, 4, 6, 7, 6, 7, 5, 5, 5, 5, 9, 8, 5, 7, 6, 7, ...
## $ A2 <int> 11, 4, 9, 8, 8, 8, 6, 7, 6, 5, 11, 8, 7, 8, 8, 5...
## $ A3 <int> 10, 4, 3, 8, 9, 10, 4, 7, 8, 4, 13, 10, 8, 9, 11...
## $ A4 <int> 11, 4, 9, 9, 9, 12, 6, 8, 9, 11, 11, 12, 8, 11, ...
## $ A5 <int> 11, 4, 6, 10, 9, 10, 8, 9, 12, 10, 14, 13, 12, 9...
## $ B1 <int> 5, 3, 6, 6, 6, 6, 3, 4, 4, 5, 6, 5, 13, 5, 5, 5,...
## $ A6 <int> 6, 4, 7, 7, 9, 8, 9, 6, 10, 6, 11, 12, 10, 9, 7,...
## $ A7 <int> 5, 6, 8, 8, 7, 10, 6, 6, 9, 8, 15, 12, 9, 7, 9, ...
## $ Recog.A <int> 10, 11, 14, 15, 12, 15, 15, 11, 12, 15, 15, 15, ...
## $ Recog.B <int> 6, 3, 8, 12, 9, 12, 6, 10, 7, 6, 12, 10, 4, 7, 1...
## $ Intrusion <int> 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, ...
## $ Perseverance <int> 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, ...
## $ Primacy <int> 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 0, ...
## $ Recency <int> 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, ...
## $ Total.RAVLT <int> 50, 20, 33, 42, 63, 47, 29, 36, 40, 35, 58, 51, ...
## $ Forgetfulness.Rate <dbl> 0.8, 1.5, 1.1, 1.1, 0.8, 1.3, 0.7, 1.0, 0.9, 1.3...
## $ Time.CW <int> 158, 108, 125, 182, 110, 136, 167, 136, 127, 142...
## $ Time.C <int> 116, 116, 116, 115, 116, 116, 116, 116, 116, 116...
## $ Digits.forward <int> 8, 7, 6, 6, 7, 5, 4, 5, 10, 6, 8, 2, 8, 6, 8, 5,...
## $ Digits.backward <int> 6, 7, 8, 3, 5, 4, 0, 5, 6, 9, 11, 4, 6, 1, 5, 1,...
## $ Span.forward <int> 6, 5, 4, 4, 6, 4, 3, 4, 6, 5, 5, 2, 5, 5, 7, 4, ...
## $ Span.backward <int> 3, 4, 5, 3, 4, 4, 0, 3, 4, 5, 7, 4, 3, 2, 3, 2, ...
## $ Corsi.forward <int> 4, 8, 9, 6, 10, 7, 6, 7, 9, 8, 10, 7, 8, 5, 7, 5...
## $ Corsi.backward <int> 2, 4, 5, 5, 6, 7, 5, 4, 4, 7, 7, 4, 8, 5, 3, 3, ...
## $ d2.RB <int> 374, 343, 388, 310, 402, 477, 208, 263, 396, 330...
## $ d2.RL <int> 360, 318, 378, 282, 393, 457, 189, 225, 382, 319...
## $ Reading.time <int> 29, 19, 17, 30, 24, 25, 25, 23, 22, 26, 17, 41, ...
## $ Count.time <int> 30, 25, 22, 43, 26, 25, 32, 30, 31, 31, 28, 47, ...
## $ Choice.time <int> 50, 40, 36, 64, 36, 44, 46, 40, 36, 55, 47, 96, ...
## $ Alternation.time <int> 59, 48, 53, 69, 44, 89, 56, 66, 52, 66, 56, 91, ...
## $ Inhibition <int> 21, 21, 19, 34, 12, 19, 21, 17, 14, 29, 30, 55, ...
## $ Flexibility <int> 30, 29, 36, 39, 20, 64, 31, 43, 30, 40, 39, 50, ...
## $ n_cat <int> 1, 3, 4, 4, 5, 3, 1, 0, 4, 3, 4, 3, 3, 2, 0, 2, ...
## $ n_erro <int> 12, 15, 6, 6, 4, 10, 16, 22, 7, 13, 10, 17, 15, ...
## $ perda_set <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, ...Descritivas (Caso vs Controle)
# Describe by Groups (Case vs. Control)
psych::describeBy(red[,c(2,3,9:19,26,27,30:46)], red$Group, tr=.2)##
## Descriptive statistics by group
## group: Case
## vars n mean sd median trimmed mad min max range
## Age 1 31 15.13 1.12 15 14.95 1.48 14.0 17.0 3.0
## Education 2 31 10.45 1.31 11 10.63 1.48 8.0 12.0 4.0
## Vocabulary 3 31 38.84 8.55 40 39.00 7.41 22.0 56.0 34.0
## Matrix.Reasoning 4 31 21.71 4.74 22 21.89 4.45 12.0 29.0 17.0
## IQ 5 31 83.55 10.30 81 82.42 11.86 70.0 104.0 34.0
## A1 6 31 6.23 1.59 6 6.05 1.48 3.0 10.0 7.0
## A2 7 31 7.68 1.68 8 7.68 1.48 4.0 11.0 7.0
## A3 8 31 8.52 2.66 9 8.84 1.48 3.0 13.0 10.0
## A4 9 31 9.81 2.15 10 10.00 2.97 4.0 13.0 9.0
## A5 10 31 10.00 2.45 10 10.26 1.48 3.0 14.0 11.0
## B1 11 31 4.97 1.99 5 4.95 1.48 1.0 13.0 12.0
## A6 12 31 8.65 2.30 9 8.74 2.97 4.0 12.0 8.0
## A7 13 31 8.61 2.62 9 8.58 2.97 4.0 15.0 11.0
## Total.RAVLT 14 31 42.90 9.22 43 43.37 8.90 20.0 63.0 43.0
## Forgetfulness.Rate 15 31 1.01 0.20 1 0.98 0.15 0.7 1.5 0.8
## Digits.forward 16 31 6.26 2.07 6 6.47 1.48 2.0 10.0 8.0
## Digits.backward 17 31 5.61 2.40 6 5.74 1.48 0.0 11.0 11.0
## Span.forward 18 31 4.55 1.26 5 4.63 1.48 2.0 7.0 5.0
## Span.backward 19 31 3.52 1.21 3 3.42 1.48 0.0 7.0 7.0
## Corsi.forward 20 31 6.94 1.48 7 6.84 1.48 4.0 10.0 6.0
## Corsi.backward 21 31 4.84 1.75 5 4.84 1.48 1.0 9.0 8.0
## d2.RB 22 31 361.48 82.24 374 357.89 94.89 208.0 531.0 323.0
## d2.RL 23 31 335.74 82.66 338 338.05 87.47 189.0 480.0 291.0
## Reading.time 24 31 24.26 5.01 24 23.74 4.45 17.0 41.0 24.0
## Count.time 25 31 30.84 5.77 30 29.95 2.97 22.0 47.0 25.0
## Choice.time 26 31 50.32 11.91 49 48.58 8.90 36.0 96.0 60.0
## Alternation.time 27 31 63.52 13.06 61 61.74 11.86 44.0 105.0 61.0
## Inhibition 28 31 26.06 9.01 26 25.58 7.41 10.0 55.0 45.0
## Flexibility 29 31 39.26 11.39 39 37.95 11.86 20.0 75.0 55.0
## n_cat 30 31 2.65 1.40 3 2.74 1.48 0.0 5.0 5.0
## n_erro 31 31 10.26 5.26 9 10.00 5.93 0.0 22.0 22.0
## perda_set 32 31 0.32 0.75 0 0.00 0.00 0.0 3.0 3.0
## skew kurtosis se
## Age 0.45 -1.26 0.20
## Education -0.50 -0.82 0.24
## Vocabulary 0.00 -0.70 1.54
## Matrix.Reasoning -0.28 -0.95 0.85
## IQ 0.38 -1.13 1.85
## A1 0.47 -0.11 0.28
## A2 -0.03 -0.41 0.30
## A3 -0.62 -0.37 0.48
## A4 -0.65 -0.03 0.39
## A5 -0.97 1.18 0.44
## B1 1.76 6.27 0.36
## A6 -0.20 -1.08 0.41
## A7 0.20 -0.39 0.47
## Total.RAVLT -0.29 0.09 1.66
## Forgetfulness.Rate 0.58 -0.42 0.04
## Digits.forward -0.42 -0.31 0.37
## Digits.backward -0.32 0.12 0.43
## Span.forward -0.30 -0.13 0.23
## Span.backward 0.07 2.03 0.22
## Corsi.forward 0.29 -0.51 0.27
## Corsi.backward 0.09 -0.07 0.31
## d2.RB 0.14 -1.04 14.77
## d2.RL -0.08 -1.14 14.85
## Reading.time 1.08 1.78 0.90
## Count.time 1.14 1.00 1.04
## Choice.time 1.79 4.58 2.14
## Alternation.time 1.28 1.76 2.34
## Inhibition 0.78 1.42 1.62
## Flexibility 1.04 1.48 2.05
## n_cat -0.22 -0.68 0.25
## n_erro 0.23 -0.85 0.94
## perda_set 2.22 4.03 0.13
## ------------------------------------------------------------
## group: Control
## vars n mean sd median trimmed mad min max range
## Age 1 14 16.00 1.18 16.5 16.20 0.74 14.0 17.0 3.0
## Education 2 14 11.07 1.38 11.5 11.30 0.74 8.0 13.0 5.0
## Vocabulary 3 14 46.29 6.96 47.0 47.10 6.67 31.0 55.0 24.0
## Matrix.Reasoning 4 14 27.57 2.56 27.0 27.70 3.71 23.0 31.0 8.0
## IQ 5 14 96.86 7.81 97.0 97.30 9.64 84.0 109.0 25.0
## A1 6 14 6.64 1.60 7.0 6.80 1.48 4.0 9.0 5.0
## A2 7 14 8.64 1.91 9.0 8.80 2.22 5.0 11.0 6.0
## A3 8 14 10.14 2.07 11.0 10.60 0.74 4.0 12.0 8.0
## A4 9 14 11.79 0.89 12.0 11.80 1.48 10.0 13.0 3.0
## A5 10 14 12.00 1.47 11.5 11.80 0.74 10.0 15.0 5.0
## B1 11 14 4.71 1.73 4.5 4.60 2.22 2.0 8.0 6.0
## A6 12 14 11.07 1.90 11.0 11.30 1.48 7.0 14.0 7.0
## A7 13 14 10.29 1.98 10.0 10.20 2.22 7.0 14.0 7.0
## Total.RAVLT 14 14 49.21 6.13 51.0 50.50 4.45 35.0 55.0 20.0
## Forgetfulness.Rate 15 14 0.94 0.12 1.0 0.95 0.15 0.7 1.1 0.4
## Digits.forward 16 14 8.21 1.85 8.0 8.20 1.48 5.0 11.0 6.0
## Digits.backward 17 14 6.29 1.94 6.5 6.30 2.22 3.0 10.0 7.0
## Span.forward 18 14 5.71 1.07 5.5 5.60 0.74 4.0 8.0 4.0
## Span.backward 19 14 4.36 0.84 4.0 4.40 1.48 3.0 6.0 3.0
## Corsi.forward 20 14 7.86 1.51 8.0 8.00 1.48 4.0 10.0 6.0
## Corsi.backward 21 14 6.71 1.90 6.0 6.70 1.48 3.0 10.0 7.0
## d2.RB 22 14 417.50 68.34 408.5 417.20 37.81 259.0 549.0 290.0
## d2.RL 23 14 406.07 69.72 400.0 408.30 44.48 251.0 527.0 276.0
## Reading.time 24 14 23.21 5.92 22.5 22.40 3.71 16.0 39.0 23.0
## Count.time 25 14 27.07 4.73 26.0 26.50 5.19 21.0 37.0 16.0
## Choice.time 26 14 39.86 7.23 38.0 39.00 7.41 32.0 52.0 20.0
## Alternation.time 27 14 50.50 9.67 49.5 50.10 13.34 38.0 66.0 28.0
## Inhibition 28 14 16.64 5.51 17.5 16.60 6.67 8.0 25.0 17.0
## Flexibility 29 14 27.29 7.47 27.5 27.80 6.67 14.0 39.0 25.0
## n_cat 30 14 3.36 1.01 3.0 3.30 1.48 2.0 5.0 3.0
## n_erro 31 14 7.71 2.67 7.0 7.70 2.97 4.0 12.0 8.0
## perda_set 32 14 0.43 0.65 0.0 0.30 0.00 0.0 2.0 2.0
## skew kurtosis se
## Age -0.53 -1.44 0.31
## Education -0.76 -0.51 0.37
## Vocabulary -0.62 -0.66 1.86
## Matrix.Reasoning -0.14 -1.58 0.69
## IQ -0.20 -1.35 2.09
## A1 -0.61 -0.95 0.43
## A2 -0.33 -1.16 0.51
## A3 -1.82 2.73 0.55
## A4 -0.22 -0.95 0.24
## A5 0.68 -0.91 0.39
## B1 0.24 -1.14 0.46
## A6 -0.59 -0.42 0.51
## A7 0.19 -0.96 0.53
## Total.RAVLT -0.94 -0.33 1.64
## Forgetfulness.Rate -0.53 -0.77 0.03
## Digits.forward 0.19 -1.04 0.49
## Digits.backward 0.04 -1.01 0.52
## Span.forward 0.53 -0.65 0.29
## Span.backward 0.06 -0.86 0.23
## Corsi.forward -0.89 0.47 0.40
## Corsi.backward 0.01 -0.88 0.51
## d2.RB -0.22 0.30 18.26
## d2.RL -0.27 -0.16 18.63
## Reading.time 1.18 1.08 1.58
## Count.time 0.56 -0.81 1.26
## Choice.time 0.45 -1.48 1.93
## Alternation.time 0.20 -1.58 2.58
## Inhibition -0.05 -1.51 1.47
## Flexibility -0.20 -1.00 2.00
## n_cat 0.15 -1.24 0.27
## n_erro 0.08 -1.47 0.71
## perda_set 1.04 -0.20 0.17Descritivas (Tipos de Abuso)
# Describe by Types (Multiple, Once, Control)
psych::describeBy(red[,c(2,3,9:19,26,27,30:46)], red$Type, tr=.2)##
## Descriptive statistics by group
## group: Control
## vars n mean sd median trimmed mad min max range
## Age 1 14 16.00 1.18 16.5 16.20 0.74 14.0 17.0 3.0
## Education 2 14 11.07 1.38 11.5 11.30 0.74 8.0 13.0 5.0
## Vocabulary 3 14 46.29 6.96 47.0 47.10 6.67 31.0 55.0 24.0
## Matrix.Reasoning 4 14 27.57 2.56 27.0 27.70 3.71 23.0 31.0 8.0
## IQ 5 14 96.86 7.81 97.0 97.30 9.64 84.0 109.0 25.0
## A1 6 14 6.64 1.60 7.0 6.80 1.48 4.0 9.0 5.0
## A2 7 14 8.64 1.91 9.0 8.80 2.22 5.0 11.0 6.0
## A3 8 14 10.14 2.07 11.0 10.60 0.74 4.0 12.0 8.0
## A4 9 14 11.79 0.89 12.0 11.80 1.48 10.0 13.0 3.0
## A5 10 14 12.00 1.47 11.5 11.80 0.74 10.0 15.0 5.0
## B1 11 14 4.71 1.73 4.5 4.60 2.22 2.0 8.0 6.0
## A6 12 14 11.07 1.90 11.0 11.30 1.48 7.0 14.0 7.0
## A7 13 14 10.29 1.98 10.0 10.20 2.22 7.0 14.0 7.0
## Total.RAVLT 14 14 49.21 6.13 51.0 50.50 4.45 35.0 55.0 20.0
## Forgetfulness.Rate 15 14 0.94 0.12 1.0 0.95 0.15 0.7 1.1 0.4
## Digits.forward 16 14 8.21 1.85 8.0 8.20 1.48 5.0 11.0 6.0
## Digits.backward 17 14 6.29 1.94 6.5 6.30 2.22 3.0 10.0 7.0
## Span.forward 18 14 5.71 1.07 5.5 5.60 0.74 4.0 8.0 4.0
## Span.backward 19 14 4.36 0.84 4.0 4.40 1.48 3.0 6.0 3.0
## Corsi.forward 20 14 7.86 1.51 8.0 8.00 1.48 4.0 10.0 6.0
## Corsi.backward 21 14 6.71 1.90 6.0 6.70 1.48 3.0 10.0 7.0
## d2.RB 22 14 417.50 68.34 408.5 417.20 37.81 259.0 549.0 290.0
## d2.RL 23 14 406.07 69.72 400.0 408.30 44.48 251.0 527.0 276.0
## Reading.time 24 14 23.21 5.92 22.5 22.40 3.71 16.0 39.0 23.0
## Count.time 25 14 27.07 4.73 26.0 26.50 5.19 21.0 37.0 16.0
## Choice.time 26 14 39.86 7.23 38.0 39.00 7.41 32.0 52.0 20.0
## Alternation.time 27 14 50.50 9.67 49.5 50.10 13.34 38.0 66.0 28.0
## Inhibition 28 14 16.64 5.51 17.5 16.60 6.67 8.0 25.0 17.0
## Flexibility 29 14 27.29 7.47 27.5 27.80 6.67 14.0 39.0 25.0
## n_cat 30 14 3.36 1.01 3.0 3.30 1.48 2.0 5.0 3.0
## n_erro 31 14 7.71 2.67 7.0 7.70 2.97 4.0 12.0 8.0
## perda_set 32 14 0.43 0.65 0.0 0.30 0.00 0.0 2.0 2.0
## skew kurtosis se
## Age -0.53 -1.44 0.31
## Education -0.76 -0.51 0.37
## Vocabulary -0.62 -0.66 1.86
## Matrix.Reasoning -0.14 -1.58 0.69
## IQ -0.20 -1.35 2.09
## A1 -0.61 -0.95 0.43
## A2 -0.33 -1.16 0.51
## A3 -1.82 2.73 0.55
## A4 -0.22 -0.95 0.24
## A5 0.68 -0.91 0.39
## B1 0.24 -1.14 0.46
## A6 -0.59 -0.42 0.51
## A7 0.19 -0.96 0.53
## Total.RAVLT -0.94 -0.33 1.64
## Forgetfulness.Rate -0.53 -0.77 0.03
## Digits.forward 0.19 -1.04 0.49
## Digits.backward 0.04 -1.01 0.52
## Span.forward 0.53 -0.65 0.29
## Span.backward 0.06 -0.86 0.23
## Corsi.forward -0.89 0.47 0.40
## Corsi.backward 0.01 -0.88 0.51
## d2.RB -0.22 0.30 18.26
## d2.RL -0.27 -0.16 18.63
## Reading.time 1.18 1.08 1.58
## Count.time 0.56 -0.81 1.26
## Choice.time 0.45 -1.48 1.93
## Alternation.time 0.20 -1.58 2.58
## Inhibition -0.05 -1.51 1.47
## Flexibility -0.20 -1.00 2.00
## n_cat 0.15 -1.24 0.27
## n_erro 0.08 -1.47 0.71
## perda_set 1.04 -0.20 0.17
## ------------------------------------------------------------
## group: Multiple
## vars n mean sd median trimmed mad min max range
## Age 1 15 15.20 0.94 15 15.22 1.48 14.0 17.0 3.0
## Education 2 15 10.73 1.16 11 10.78 1.48 8.0 12.0 4.0
## Vocabulary 3 15 37.00 7.47 36 36.89 5.93 25.0 51.0 26.0
## Matrix.Reasoning 4 15 20.80 4.89 21 20.89 4.45 12.0 29.0 17.0
## IQ 5 15 81.00 8.90 80 79.56 10.38 71.0 100.0 29.0
## A1 6 15 6.27 1.87 6 6.00 1.48 3.0 10.0 7.0
## A2 7 15 7.93 1.33 8 8.00 1.48 6.0 10.0 4.0
## A3 8 15 8.93 2.22 9 9.11 1.48 3.0 12.0 9.0
## A4 9 15 10.27 1.98 10 10.44 2.97 6.0 13.0 7.0
## A5 10 15 10.27 2.46 11 10.67 1.48 3.0 14.0 11.0
## B1 11 15 4.47 1.60 4 4.56 1.48 1.0 7.0 6.0
## A6 12 15 9.20 2.43 9 9.56 2.97 5.0 12.0 7.0
## A7 13 15 8.93 2.79 10 9.44 1.48 4.0 13.0 9.0
## Total.RAVLT 14 15 43.67 7.65 44 44.22 5.93 25.0 53.0 28.0
## Forgetfulness.Rate 15 15 0.96 0.14 1 0.97 0.15 0.7 1.2 0.5
## Digits.forward 16 15 6.20 2.27 7 6.56 1.48 2.0 10.0 8.0
## Digits.backward 17 15 6.20 1.52 6 6.22 1.48 3.0 9.0 6.0
## Span.forward 18 15 4.40 1.30 5 4.67 0.00 2.0 7.0 5.0
## Span.backward 19 15 3.53 0.74 3 3.33 0.00 3.0 5.0 2.0
## Corsi.forward 20 15 6.60 1.06 7 6.56 1.48 5.0 9.0 4.0
## Corsi.backward 21 15 4.73 1.87 5 4.89 1.48 1.0 9.0 8.0
## d2.RB 22 15 381.93 88.50 377 380.11 123.06 265.0 531.0 266.0
## d2.RL 23 15 351.53 86.20 368 355.00 88.96 192.0 480.0 288.0
## Reading.time 24 15 23.93 3.90 24 23.56 4.45 19.0 30.0 11.0
## Count.time 25 15 30.20 4.00 30 30.22 2.97 24.0 38.0 14.0
## Choice.time 26 15 51.33 8.16 50 50.78 7.41 40.0 68.0 28.0
## Alternation.time 27 15 61.53 7.10 61 61.67 8.90 51.0 72.0 21.0
## Inhibition 28 15 27.40 7.88 28 28.22 8.90 10.0 38.0 28.0
## Flexibility 29 15 37.60 8.23 38 37.67 8.90 25.0 52.0 27.0
## n_cat 30 15 2.67 1.35 3 2.56 1.48 0.0 5.0 5.0
## n_erro 31 15 9.93 5.02 9 9.44 5.93 4.0 19.0 15.0
## perda_set 32 15 0.47 0.74 0 0.22 0.00 0.0 2.0 2.0
## skew kurtosis se
## Age 0.12 -1.23 0.24
## Education -0.53 -0.43 0.30
## Vocabulary 0.20 -0.89 1.93
## Matrix.Reasoning -0.13 -0.91 1.26
## IQ 0.60 -0.92 2.30
## A1 0.43 -0.54 0.48
## A2 -0.06 -1.24 0.34
## A3 -0.95 1.03 0.57
## A4 -0.40 -0.72 0.51
## A5 -1.46 2.51 0.64
## B1 -0.34 -0.73 0.41
## A6 -0.47 -1.18 0.63
## A7 -0.58 -0.97 0.72
## Total.RAVLT -0.72 0.01 1.98
## Forgetfulness.Rate -0.19 -1.11 0.04
## Digits.forward -0.47 -0.75 0.59
## Digits.backward -0.20 -0.34 0.39
## Span.forward -0.34 -0.25 0.34
## Span.backward 0.87 -0.78 0.19
## Corsi.forward 0.44 -0.27 0.27
## Corsi.backward 0.06 0.27 0.48
## d2.RB 0.07 -1.56 22.85
## d2.RL -0.19 -1.23 22.26
## Reading.time 0.25 -1.48 1.01
## Count.time 0.16 -0.92 1.03
## Choice.time 0.50 -0.52 2.11
## Alternation.time -0.09 -1.59 1.83
## Inhibition -0.58 -0.65 2.03
## Flexibility 0.03 -1.11 2.12
## n_cat 0.08 -0.52 0.35
## n_erro 0.31 -1.44 1.30
## perda_set 1.08 -0.43 0.19
## ------------------------------------------------------------
## group: Once
## vars n mean sd median trimmed mad min max range
## Age 1 16 15.06 1.29 14.5 14.80 0.74 14.0 17.0 3.0
## Education 2 16 10.19 1.42 10.5 10.30 1.48 8.0 12.0 4.0
## Vocabulary 3 16 40.56 9.35 42.0 41.10 4.45 22.0 56.0 34.0
## Matrix.Reasoning 4 16 22.56 4.59 24.0 23.00 4.45 14.0 29.0 15.0
## IQ 5 16 85.94 11.20 87.0 85.90 14.08 70.0 104.0 34.0
## A1 6 16 6.19 1.33 6.0 6.10 1.48 4.0 9.0 5.0
## A2 7 16 7.44 1.97 8.0 7.40 1.48 4.0 11.0 7.0
## A3 8 16 8.12 3.03 8.5 8.30 2.22 3.0 13.0 10.0
## A4 9 16 9.38 2.28 9.0 9.60 2.97 4.0 12.0 8.0
## A5 10 16 9.75 2.49 10.0 9.90 1.48 4.0 14.0 10.0
## B1 11 16 5.44 2.25 5.0 5.20 1.48 3.0 13.0 10.0
## A6 12 16 8.12 2.13 8.5 8.10 2.22 4.0 12.0 8.0
## A7 13 16 8.31 2.50 8.0 7.90 1.48 5.0 15.0 10.0
## Total.RAVLT 14 16 42.19 10.69 41.5 42.10 8.90 20.0 63.0 43.0
## Forgetfulness.Rate 15 16 1.05 0.24 1.0 1.03 0.30 0.7 1.5 0.8
## Digits.forward 16 16 6.31 1.92 6.0 6.40 1.48 2.0 10.0 8.0
## Digits.backward 17 16 5.06 2.95 5.0 5.10 2.22 0.0 11.0 11.0
## Span.forward 18 16 4.69 1.25 5.0 4.70 1.48 2.0 7.0 5.0
## Span.backward 19 16 3.50 1.55 3.5 3.50 0.74 0.0 7.0 7.0
## Corsi.forward 20 16 7.25 1.77 7.0 7.30 1.48 4.0 10.0 6.0
## Corsi.backward 21 16 4.94 1.69 5.0 4.90 1.48 2.0 8.0 6.0
## d2.RB 22 16 342.31 73.54 336.5 344.00 92.66 208.0 477.0 269.0
## d2.RL 23 16 320.94 79.03 318.5 323.70 102.30 189.0 457.0 268.0
## Reading.time 24 16 24.56 5.98 23.5 23.90 4.45 17.0 41.0 24.0
## Count.time 25 16 31.44 7.13 30.0 29.70 2.97 22.0 47.0 25.0
## Choice.time 26 16 49.38 14.82 46.5 46.30 9.64 36.0 96.0 60.0
## Alternation.time 27 16 65.38 16.92 62.5 61.70 12.60 44.0 105.0 61.0
## Inhibition 28 16 24.81 10.04 23.0 23.50 7.41 12.0 55.0 43.0
## Flexibility 29 16 40.81 13.82 39.0 38.50 11.86 20.0 75.0 55.0
## n_cat 30 16 2.62 1.50 3.0 2.80 1.48 0.0 5.0 5.0
## n_erro 31 16 10.56 5.62 10.0 10.40 5.93 0.0 22.0 22.0
## perda_set 32 16 0.19 0.75 0.0 0.00 0.00 0.0 3.0 3.0
## skew kurtosis se
## Age 0.59 -1.48 0.32
## Education -0.31 -1.37 0.36
## Vocabulary -0.29 -0.73 2.34
## Matrix.Reasoning -0.37 -1.27 1.15
## IQ 0.07 -1.43 2.80
## A1 0.32 -0.82 0.33
## A2 0.16 -0.71 0.49
## A3 -0.29 -1.18 0.76
## A4 -0.69 -0.34 0.57
## A5 -0.46 -0.08 0.62
## B1 2.18 5.17 0.56
## A6 -0.04 -0.93 0.53
## A7 1.11 0.88 0.62
## Total.RAVLT -0.02 -0.39 2.67
## Forgetfulness.Rate 0.34 -1.33 0.06
## Digits.forward -0.26 -0.25 0.48
## Digits.backward 0.07 -0.71 0.74
## Span.forward -0.21 -0.47 0.31
## Span.backward 0.00 0.48 0.39
## Corsi.forward -0.08 -1.08 0.44
## Corsi.backward 0.17 -1.10 0.42
## d2.RB -0.06 -1.07 18.38
## d2.RL -0.05 -1.35 19.76
## Reading.time 1.08 1.07 1.49
## Count.time 0.98 -0.24 1.78
## Choice.time 1.85 3.34 3.71
## Alternation.time 0.89 -0.25 4.23
## Inhibition 1.49 2.45 2.51
## Flexibility 0.92 0.27 3.46
## n_cat -0.39 -1.08 0.38
## n_erro 0.13 -0.75 1.41
## perda_set 3.28 9.36 0.19Comparacao entre os Tipos
## Robust statistics
library(WRS2)
# Function to calculate 20% trimmed mean
tmean <- function(x,tr=.2,na.rm=FALSE,STAND=NULL){
if(na.rm)x<-x[!is.na(x)]
val<-mean(x,tr)
val
}
# Function to calculate 20% trimmed standard deviation (SD)
sd_trim <- function(x,trim=0.2, const=TRUE){
# trimmed sd, where x is a matrix (column-wise)
x <- as.matrix(x)
if (const){
if (trim==0.1){const <- 0.7892}
else if (trim==0.2){const <- 0.6615}
else {warning("Did you specify the correct consistency constant for trimming?")}
}
else{const <- 1}
m <- apply(x,2,mean,trim)
res <- x-rep(1,nrow(x))%*%t(m)
qu <- apply(abs(res),2,quantile,1-trim)
sdtrim <- apply(matrix(res[t(abs(t(res))<=qu)]^2,ncol=ncol(x),byrow=FALSE),2,sum)
sdtrim <- sqrt(sdtrim/((nrow(x)*(1-trim)-1)))/const
return(sdtrim)
}
# Select variables to compare Types (Some vars were not collected in Control)
# Depersonalization, Derealization, Dissociation
BD <- red[,c(2:3,4,9:46)]
psych::describeBy(BD, BD$Type, tr=.2)##
## Descriptive statistics by group
## group: Control
## vars n mean sd median trimmed mad min max range
## Age 1 14 16.00 1.18 16.5 16.20 0.74 14.0 17.0 3.0
## Education 2 14 11.07 1.38 11.5 11.30 0.74 8.0 13.0 5.0
## Type* 3 14 1.00 0.00 1.0 1.00 0.00 1.0 1.0 0.0
## Vocabulary 4 14 46.29 6.96 47.0 47.10 6.67 31.0 55.0 24.0
## Matrix.Reasoning 5 14 27.57 2.56 27.0 27.70 3.71 23.0 31.0 8.0
## IQ 6 14 96.86 7.81 97.0 97.30 9.64 84.0 109.0 25.0
## A1 7 14 6.64 1.60 7.0 6.80 1.48 4.0 9.0 5.0
## A2 8 14 8.64 1.91 9.0 8.80 2.22 5.0 11.0 6.0
## A3 9 14 10.14 2.07 11.0 10.60 0.74 4.0 12.0 8.0
## A4 10 14 11.79 0.89 12.0 11.80 1.48 10.0 13.0 3.0
## A5 11 14 12.00 1.47 11.5 11.80 0.74 10.0 15.0 5.0
## B1 12 14 4.71 1.73 4.5 4.60 2.22 2.0 8.0 6.0
## A6 13 14 11.07 1.90 11.0 11.30 1.48 7.0 14.0 7.0
## A7 14 14 10.29 1.98 10.0 10.20 2.22 7.0 14.0 7.0
## Recog.A 15 14 14.50 0.85 15.0 14.70 0.00 12.0 15.0 3.0
## Recog.B 16 14 9.50 2.07 10.0 9.60 2.97 6.0 12.0 6.0
## Intrusion 17 14 0.57 0.51 1.0 0.60 0.00 0.0 1.0 1.0
## Perseverance 18 14 1.00 0.00 1.0 1.00 0.00 1.0 1.0 0.0
## Primacy 19 14 0.36 0.50 0.0 0.30 0.00 0.0 1.0 1.0
## Recency 20 14 0.14 0.36 0.0 0.00 0.00 0.0 1.0 1.0
## Total.RAVLT 21 14 49.21 6.13 51.0 50.50 4.45 35.0 55.0 20.0
## Forgetfulness.Rate 22 14 0.94 0.12 1.0 0.95 0.15 0.7 1.1 0.4
## Time.CW 23 14 122.86 29.06 122.0 121.80 28.91 75.0 177.0 102.0
## Time.C 24 14 115.71 0.47 116.0 115.80 0.00 115.0 116.0 1.0
## Digits.forward 25 14 8.21 1.85 8.0 8.20 1.48 5.0 11.0 6.0
## Digits.backward 26 14 6.29 1.94 6.5 6.30 2.22 3.0 10.0 7.0
## Span.forward 27 14 5.71 1.07 5.5 5.60 0.74 4.0 8.0 4.0
## Span.backward 28 14 4.36 0.84 4.0 4.40 1.48 3.0 6.0 3.0
## Corsi.forward 29 14 7.86 1.51 8.0 8.00 1.48 4.0 10.0 6.0
## Corsi.backward 30 14 6.71 1.90 6.0 6.70 1.48 3.0 10.0 7.0
## d2.RB 31 14 417.50 68.34 408.5 417.20 37.81 259.0 549.0 290.0
## d2.RL 32 14 406.07 69.72 400.0 408.30 44.48 251.0 527.0 276.0
## Reading.time 33 14 23.21 5.92 22.5 22.40 3.71 16.0 39.0 23.0
## Count.time 34 14 27.07 4.73 26.0 26.50 5.19 21.0 37.0 16.0
## Choice.time 35 14 39.86 7.23 38.0 39.00 7.41 32.0 52.0 20.0
## Alternation.time 36 14 50.50 9.67 49.5 50.10 13.34 38.0 66.0 28.0
## Inhibition 37 14 16.64 5.51 17.5 16.60 6.67 8.0 25.0 17.0
## Flexibility 38 14 27.29 7.47 27.5 27.80 6.67 14.0 39.0 25.0
## n_cat 39 14 3.36 1.01 3.0 3.30 1.48 2.0 5.0 3.0
## n_erro 40 14 7.71 2.67 7.0 7.70 2.97 4.0 12.0 8.0
## perda_set 41 14 0.43 0.65 0.0 0.30 0.00 0.0 2.0 2.0
## skew kurtosis se
## Age -0.53 -1.44 0.31
## Education -0.76 -0.51 0.37
## Type* NaN NaN 0.00
## Vocabulary -0.62 -0.66 1.86
## Matrix.Reasoning -0.14 -1.58 0.69
## IQ -0.20 -1.35 2.09
## A1 -0.61 -0.95 0.43
## A2 -0.33 -1.16 0.51
## A3 -1.82 2.73 0.55
## A4 -0.22 -0.95 0.24
## A5 0.68 -0.91 0.39
## B1 0.24 -1.14 0.46
## A6 -0.59 -0.42 0.51
## A7 0.19 -0.96 0.53
## Recog.A -1.72 2.33 0.23
## Recog.B -0.15 -1.45 0.55
## Intrusion -0.26 -2.07 0.14
## Perseverance NaN NaN 0.00
## Primacy 0.53 -1.83 0.13
## Recency 1.83 1.45 0.10
## Total.RAVLT -0.94 -0.33 1.64
## Forgetfulness.Rate -0.53 -0.77 0.03
## Time.CW 0.22 -0.94 7.77
## Time.C -0.85 -1.36 0.13
## Digits.forward 0.19 -1.04 0.49
## Digits.backward 0.04 -1.01 0.52
## Span.forward 0.53 -0.65 0.29
## Span.backward 0.06 -0.86 0.23
## Corsi.forward -0.89 0.47 0.40
## Corsi.backward 0.01 -0.88 0.51
## d2.RB -0.22 0.30 18.26
## d2.RL -0.27 -0.16 18.63
## Reading.time 1.18 1.08 1.58
## Count.time 0.56 -0.81 1.26
## Choice.time 0.45 -1.48 1.93
## Alternation.time 0.20 -1.58 2.58
## Inhibition -0.05 -1.51 1.47
## Flexibility -0.20 -1.00 2.00
## n_cat 0.15 -1.24 0.27
## n_erro 0.08 -1.47 0.71
## perda_set 1.04 -0.20 0.17
## ------------------------------------------------------------
## group: Multiple
## vars n mean sd median trimmed mad min max range
## Age 1 15 15.20 0.94 15 15.22 1.48 14.0 17.0 3.0
## Education 2 15 10.73 1.16 11 10.78 1.48 8.0 12.0 4.0
## Type* 3 15 1.00 0.00 1 1.00 0.00 1.0 1.0 0.0
## Vocabulary 4 15 37.00 7.47 36 36.89 5.93 25.0 51.0 26.0
## Matrix.Reasoning 5 15 20.80 4.89 21 20.89 4.45 12.0 29.0 17.0
## IQ 6 15 81.00 8.90 80 79.56 10.38 71.0 100.0 29.0
## A1 7 15 6.27 1.87 6 6.00 1.48 3.0 10.0 7.0
## A2 8 15 7.93 1.33 8 8.00 1.48 6.0 10.0 4.0
## A3 9 15 8.93 2.22 9 9.11 1.48 3.0 12.0 9.0
## A4 10 15 10.27 1.98 10 10.44 2.97 6.0 13.0 7.0
## A5 11 15 10.27 2.46 11 10.67 1.48 3.0 14.0 11.0
## B1 12 15 4.47 1.60 4 4.56 1.48 1.0 7.0 6.0
## A6 13 15 9.20 2.43 9 9.56 2.97 5.0 12.0 7.0
## A7 14 15 8.93 2.79 10 9.44 1.48 4.0 13.0 9.0
## Recog.A 15 15 13.73 1.39 14 14.00 1.48 11.0 15.0 4.0
## Recog.B 16 15 8.53 2.13 9 8.67 1.48 3.0 12.0 9.0
## Intrusion 17 15 0.60 0.51 1 0.67 0.00 0.0 1.0 1.0
## Perseverance 18 15 0.93 0.26 1 1.00 0.00 0.0 1.0 1.0
## Primacy 19 15 0.27 0.46 0 0.11 0.00 0.0 1.0 1.0
## Recency 20 15 0.07 0.26 0 0.00 0.00 0.0 1.0 1.0
## Total.RAVLT 21 15 43.67 7.65 44 44.22 5.93 25.0 53.0 28.0
## Forgetfulness.Rate 22 15 0.96 0.14 1 0.97 0.15 0.7 1.2 0.5
## Time.CW 23 15 143.07 25.19 141 142.89 35.58 108.0 179.0 71.0
## Time.C 24 15 115.73 0.46 116 115.89 0.00 115.0 116.0 1.0
## Digits.forward 25 15 6.20 2.27 7 6.56 1.48 2.0 10.0 8.0
## Digits.backward 26 15 6.20 1.52 6 6.22 1.48 3.0 9.0 6.0
## Span.forward 27 15 4.40 1.30 5 4.67 0.00 2.0 7.0 5.0
## Span.backward 28 15 3.53 0.74 3 3.33 0.00 3.0 5.0 2.0
## Corsi.forward 29 15 6.60 1.06 7 6.56 1.48 5.0 9.0 4.0
## Corsi.backward 30 15 4.73 1.87 5 4.89 1.48 1.0 9.0 8.0
## d2.RB 31 15 381.93 88.50 377 380.11 123.06 265.0 531.0 266.0
## d2.RL 32 15 351.53 86.20 368 355.00 88.96 192.0 480.0 288.0
## Reading.time 33 15 23.93 3.90 24 23.56 4.45 19.0 30.0 11.0
## Count.time 34 15 30.20 4.00 30 30.22 2.97 24.0 38.0 14.0
## Choice.time 35 15 51.33 8.16 50 50.78 7.41 40.0 68.0 28.0
## Alternation.time 36 15 61.53 7.10 61 61.67 8.90 51.0 72.0 21.0
## Inhibition 37 15 27.40 7.88 28 28.22 8.90 10.0 38.0 28.0
## Flexibility 38 15 37.60 8.23 38 37.67 8.90 25.0 52.0 27.0
## n_cat 39 15 2.67 1.35 3 2.56 1.48 0.0 5.0 5.0
## n_erro 40 15 9.93 5.02 9 9.44 5.93 4.0 19.0 15.0
## perda_set 41 15 0.47 0.74 0 0.22 0.00 0.0 2.0 2.0
## skew kurtosis se
## Age 0.12 -1.23 0.24
## Education -0.53 -0.43 0.30
## Type* NaN NaN 0.00
## Vocabulary 0.20 -0.89 1.93
## Matrix.Reasoning -0.13 -0.91 1.26
## IQ 0.60 -0.92 2.30
## A1 0.43 -0.54 0.48
## A2 -0.06 -1.24 0.34
## A3 -0.95 1.03 0.57
## A4 -0.40 -0.72 0.51
## A5 -1.46 2.51 0.64
## B1 -0.34 -0.73 0.41
## A6 -0.47 -1.18 0.63
## A7 -0.58 -0.97 0.72
## Recog.A -0.75 -0.69 0.36
## Recog.B -0.78 0.70 0.55
## Intrusion -0.37 -1.98 0.13
## Perseverance -3.13 8.39 0.07
## Primacy 0.95 -1.16 0.12
## Recency 3.13 8.39 0.07
## Total.RAVLT -0.72 0.01 1.98
## Forgetfulness.Rate -0.19 -1.11 0.04
## Time.CW 0.03 -1.69 6.51
## Time.C -0.95 -1.16 0.12
## Digits.forward -0.47 -0.75 0.59
## Digits.backward -0.20 -0.34 0.39
## Span.forward -0.34 -0.25 0.34
## Span.backward 0.87 -0.78 0.19
## Corsi.forward 0.44 -0.27 0.27
## Corsi.backward 0.06 0.27 0.48
## d2.RB 0.07 -1.56 22.85
## d2.RL -0.19 -1.23 22.26
## Reading.time 0.25 -1.48 1.01
## Count.time 0.16 -0.92 1.03
## Choice.time 0.50 -0.52 2.11
## Alternation.time -0.09 -1.59 1.83
## Inhibition -0.58 -0.65 2.03
## Flexibility 0.03 -1.11 2.12
## n_cat 0.08 -0.52 0.35
## n_erro 0.31 -1.44 1.30
## perda_set 1.08 -0.43 0.19
## ------------------------------------------------------------
## group: Once
## vars n mean sd median trimmed mad min max range
## Age 1 16 15.06 1.29 14.5 14.80 0.74 14.0 17.0 3.0
## Education 2 16 10.19 1.42 10.5 10.30 1.48 8.0 12.0 4.0
## Type* 3 16 1.00 0.00 1.0 1.00 0.00 1.0 1.0 0.0
## Vocabulary 4 16 40.56 9.35 42.0 41.10 4.45 22.0 56.0 34.0
## Matrix.Reasoning 5 16 22.56 4.59 24.0 23.00 4.45 14.0 29.0 15.0
## IQ 6 16 85.94 11.20 87.0 85.90 14.08 70.0 104.0 34.0
## A1 7 16 6.19 1.33 6.0 6.10 1.48 4.0 9.0 5.0
## A2 8 16 7.44 1.97 8.0 7.40 1.48 4.0 11.0 7.0
## A3 9 16 8.12 3.03 8.5 8.30 2.22 3.0 13.0 10.0
## A4 10 16 9.38 2.28 9.0 9.60 2.97 4.0 12.0 8.0
## A5 11 16 9.75 2.49 10.0 9.90 1.48 4.0 14.0 10.0
## B1 12 16 5.44 2.25 5.0 5.20 1.48 3.0 13.0 10.0
## A6 13 16 8.12 2.13 8.5 8.10 2.22 4.0 12.0 8.0
## A7 14 16 8.31 2.50 8.0 7.90 1.48 5.0 15.0 10.0
## Recog.A 15 16 13.31 2.12 14.5 13.80 0.74 9.0 15.0 6.0
## Recog.B 16 16 8.12 2.78 8.0 8.10 2.97 3.0 12.0 9.0
## Intrusion 17 16 0.44 0.51 0.0 0.40 0.00 0.0 1.0 1.0
## Perseverance 18 16 0.75 0.45 1.0 0.90 0.00 0.0 1.0 1.0
## Primacy 19 16 0.25 0.45 0.0 0.10 0.00 0.0 1.0 1.0
## Recency 20 16 0.12 0.34 0.0 0.00 0.00 0.0 1.0 1.0
## Total.RAVLT 21 16 42.19 10.69 41.5 42.10 8.90 20.0 63.0 43.0
## Forgetfulness.Rate 22 16 1.05 0.24 1.0 1.03 0.30 0.7 1.5 0.8
## Time.CW 23 16 144.62 29.33 136.0 143.50 35.58 101.0 191.0 90.0
## Time.C 24 16 115.62 1.02 116.0 116.00 0.00 112.0 116.0 4.0
## Digits.forward 25 16 6.31 1.92 6.0 6.40 1.48 2.0 10.0 8.0
## Digits.backward 26 16 5.06 2.95 5.0 5.10 2.22 0.0 11.0 11.0
## Span.forward 27 16 4.69 1.25 5.0 4.70 1.48 2.0 7.0 5.0
## Span.backward 28 16 3.50 1.55 3.5 3.50 0.74 0.0 7.0 7.0
## Corsi.forward 29 16 7.25 1.77 7.0 7.30 1.48 4.0 10.0 6.0
## Corsi.backward 30 16 4.94 1.69 5.0 4.90 1.48 2.0 8.0 6.0
## d2.RB 31 16 342.31 73.54 336.5 344.00 92.66 208.0 477.0 269.0
## d2.RL 32 16 320.94 79.03 318.5 323.70 102.30 189.0 457.0 268.0
## Reading.time 33 16 24.56 5.98 23.5 23.90 4.45 17.0 41.0 24.0
## Count.time 34 16 31.44 7.13 30.0 29.70 2.97 22.0 47.0 25.0
## Choice.time 35 16 49.38 14.82 46.5 46.30 9.64 36.0 96.0 60.0
## Alternation.time 36 16 65.38 16.92 62.5 61.70 12.60 44.0 105.0 61.0
## Inhibition 37 16 24.81 10.04 23.0 23.50 7.41 12.0 55.0 43.0
## Flexibility 38 16 40.81 13.82 39.0 38.50 11.86 20.0 75.0 55.0
## n_cat 39 16 2.62 1.50 3.0 2.80 1.48 0.0 5.0 5.0
## n_erro 40 16 10.56 5.62 10.0 10.40 5.93 0.0 22.0 22.0
## perda_set 41 16 0.19 0.75 0.0 0.00 0.00 0.0 3.0 3.0
## skew kurtosis se
## Age 0.59 -1.48 0.32
## Education -0.31 -1.37 0.36
## Type* NaN NaN 0.00
## Vocabulary -0.29 -0.73 2.34
## Matrix.Reasoning -0.37 -1.27 1.15
## IQ 0.07 -1.43 2.80
## A1 0.32 -0.82 0.33
## A2 0.16 -0.71 0.49
## A3 -0.29 -1.18 0.76
## A4 -0.69 -0.34 0.57
## A5 -0.46 -0.08 0.62
## B1 2.18 5.17 0.56
## A6 -0.04 -0.93 0.53
## A7 1.11 0.88 0.62
## Recog.A -0.70 -1.16 0.53
## Recog.B -0.12 -1.15 0.69
## Intrusion 0.23 -2.07 0.13
## Perseverance -1.05 -0.95 0.11
## Primacy 1.05 -0.95 0.11
## Recency 2.06 2.40 0.09
## Total.RAVLT -0.02 -0.39 2.67
## Forgetfulness.Rate 0.34 -1.33 0.06
## Time.CW 0.23 -1.41 7.33
## Time.C -2.76 6.82 0.26
## Digits.forward -0.26 -0.25 0.48
## Digits.backward 0.07 -0.71 0.74
## Span.forward -0.21 -0.47 0.31
## Span.backward 0.00 0.48 0.39
## Corsi.forward -0.08 -1.08 0.44
## Corsi.backward 0.17 -1.10 0.42
## d2.RB -0.06 -1.07 18.38
## d2.RL -0.05 -1.35 19.76
## Reading.time 1.08 1.07 1.49
## Count.time 0.98 -0.24 1.78
## Choice.time 1.85 3.34 3.71
## Alternation.time 0.89 -0.25 4.23
## Inhibition 1.49 2.45 2.51
## Flexibility 0.92 0.27 3.46
## n_cat -0.39 -1.08 0.38
## n_erro 0.13 -0.75 1.41
## perda_set 3.28 9.36 0.19Outra comparacao entre os Tipos
library(compareGroups)
categ <- compareGroups(Type ~ ., data = red, method = 4) # 4 which performs a Shapiro-Wilks test to decide between normal or non-normal
categ##
##
## -------- Summary of results by groups of 'Type'---------
##
##
## var N p.value method selection
## 1 Group 45 <0.001** categorical ALL
## 2 Age 45 0.073* continuous non-normal ALL
## 3 Education 45 0.192 continuous non-normal ALL
## 4 Quesi 45 <0.001** continuous non-normal ALL
## 5 Depersonalization 45 0.010** continuous non-normal ALL
## 6 Derealization 45 0.010** continuous non-normal ALL
## 7 Dissociation 45 0.002** continuous non-normal ALL
## 8 Vocabulary 45 0.007** continuous non-normal ALL
## 9 Matrix.Reasoning 45 <0.001** continuous non-normal ALL
## 10 IQ 45 0.001** continuous non-normal ALL
## 11 A1 45 0.456 continuous non-normal ALL
## 12 A2 45 0.188 continuous non-normal ALL
## 13 A3 45 0.050* continuous non-normal ALL
## 14 A4 45 0.004** continuous non-normal ALL
## 15 A5 45 0.011** continuous non-normal ALL
## 16 B1 45 0.544 continuous non-normal ALL
## 17 A6 45 0.003** continuous non-normal ALL
## 18 A7 45 0.046** continuous non-normal ALL
## 19 Recog.A 45 0.238 continuous non-normal ALL
## 20 Recog.B 45 0.325 continuous non-normal ALL
## 21 Intrusion 45 0.632 continuous non-normal ALL
## 22 Perseverance 45 0.080* continuous non-normal ALL
## 23 Primacy 45 0.794 continuous non-normal ALL
## 24 Recency 45 0.793 continuous non-normal ALL
## 25 Total.RAVLT 45 0.035** continuous non-normal ALL
## 26 Forgetfulness.Rate 45 0.571 continuous non-normal ALL
## 27 Time.CW 45 0.101 continuous non-normal ALL
## 28 Time.C 45 0.866 continuous non-normal ALL
## 29 Digits.forward 45 0.023** continuous non-normal ALL
## 30 Digits.backward 45 0.278 continuous non-normal ALL
## 31 Span.forward 45 0.016** continuous non-normal ALL
## 32 Span.backward 45 0.032** continuous non-normal ALL
## 33 Corsi.forward 45 0.041** continuous non-normal ALL
## 34 Corsi.backward 45 0.011** continuous non-normal ALL
## 35 d2.RB 45 0.054* continuous non-normal ALL
## 36 d2.RL 45 0.017** continuous non-normal ALL
## 37 Reading.time 45 0.665 continuous non-normal ALL
## 38 Count.time 45 0.100* continuous non-normal ALL
## 39 Choice.time 45 0.003** continuous non-normal ALL
## 40 Alternation.time 45 0.006** continuous non-normal ALL
## 41 Inhibition 45 0.001** continuous non-normal ALL
## 42 Flexibility 45 0.002** continuous non-normal ALL
## 43 n_cat 45 0.280 continuous non-normal ALL
## 44 n_erro 45 0.295 continuous non-normal ALL
## 45 perda_set 45 0.162 continuous non-normal ALL
## -----
## Signif. codes: 0 '**' 0.05 '*' 0.1 ' ' 1restab <- createTable(categ, show.ratio = TRUE, hide.no = 'no')
update(restab, x = update(categ, ~ . ))##
## --------Summary descriptives table ---------
##
## ______________________________________
## [ALL] N
## N=45
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## Group:
## Case 31 (68.9%) 45
## Control 14 (31.1%)
## Age 15.0 [14.0;17.0] 45
## Education 11.0 [10.0;12.0] 45
## Type:
## Control 14 (31.1%) 45
## Multiple 15 (33.3%)
## Once 16 (35.6%)
## Quesi 50.0 [44.0;60.0] 45
## Depersonalization 0.00 [0.00;1.00] 45
## Derealization 0.00 [0.00;1.00] 45
## Dissociation 0.00 [0.00;2.00] 45
## Vocabulary 42.0 [35.0;48.0] 45
## Matrix.Reasoning 25.0 [20.0;27.0] 45
## IQ 87.0 [78.0;98.0] 45
## A1 6.00 [5.00;7.00] 45
## A2 8.00 [7.00;9.00] 45
## A3 9.00 [8.00;11.0] 45
## A4 11.0 [9.00;12.0] 45
## A5 11.0 [10.0;12.0] 45
## B1 5.00 [4.00;6.00] 45
## A6 10.0 [8.00;11.0] 45
## A7 9.00 [8.00;10.0] 45
## Recog.A 15.0 [13.0;15.0] 45
## Recog.B 9.00 [7.00;10.0] 45
## Intrusion 1.00 [0.00;1.00] 45
## Perseverance 1.00 [1.00;1.00] 45
## Primacy 0.00 [0.00;1.00] 45
## Recency 0.00 [0.00;0.00] 45
## Total.RAVLT 45.0 [40.0;52.0] 45
## Forgetfulness.Rate 1.00 [0.90;1.10] 45
## Time.CW 135 [114;165] 45
## Time.C 116 [116;116] 45
## Digits.forward 7.00 [6.00;8.00] 45
## Digits.backward 6.00 [5.00;7.00] 45
## Span.forward 5.00 [4.00;6.00] 45
## Span.backward 4.00 [3.00;4.00] 45
## Corsi.forward 7.00 [6.00;8.00] 45
## Corsi.backward 5.00 [4.00;6.00] 45
## d2.RB 388 [312;426] 45
## d2.RL 381 [282;406] 45
## Reading.time 23.0 [20.0;26.0] 45
## Count.time 30.0 [25.0;32.0] 45
## Choice.time 46.0 [40.0;52.0] 45
## Alternation.time 58.0 [51.0;66.0] 45
## Inhibition 21.0 [17.0;29.0] 45
## Flexibility 36.0 [29.0;41.0] 45
## n_cat 3.00 [2.00;4.00] 45
## n_erro 9.00 [6.00;13.0] 45
## perda_set 0.00 [0.00;0.00] 45
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯update(restab, show.n=TRUE)##
## --------Summary descriptives table by 'Type'---------
##
## __________________________________________________________________________________
## Control Multiple Once p.overall N
## N=14 N=15 N=16
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## Group: <0.001 45
## Case 0 (0.00%) 15 (100%) 16 (100%)
## Control 14 (100%) 0 (0.00%) 0 (0.00%)
## Age 16.5 [15.0;17.0] 15.0 [14.5;16.0] 14.5 [14.0;16.2] 0.073 45
## Education 11.5 [10.2;12.0] 11.0 [10.0;12.0] 10.5 [9.00;11.0] 0.192 45
## Quesi 45.0 [43.0;45.8] 61.0 [53.5;75.0] 51.5 [41.5;57.8] <0.001 45
## Depersonalization 0.00 [0.00;0.00] 0.00 [0.00;1.00] 0.50 [0.00;2.00] 0.010 45
## Derealization 0.00 [0.00;0.00] 0.00 [0.00;1.00] 0.50 [0.00;2.00] 0.010 45
## Dissociation 0.00 [0.00;0.00] 1.00 [0.00;2.00] 1.50 [0.00;3.25] 0.002 45
## Vocabulary 47.0 [43.2;51.8] 36.0 [33.5;41.0] 42.0 [36.8;44.2] 0.007 45
## Matrix.Reasoning 27.0 [26.0;30.0] 21.0 [17.5;23.5] 24.0 [18.8;25.5] <0.001 45
## IQ 97.0 [90.8;103] 80.0 [73.0;87.0] 87.0 [77.8;95.8] 0.001 45
## A1 7.00 [6.25;7.75] 6.00 [5.50;6.50] 6.00 [5.00;7.00] 0.456 45
## A2 9.00 [7.25;10.0] 8.00 [7.00;9.00] 8.00 [6.00;8.00] 0.188 45
## A3 11.0 [10.0;11.0] 9.00 [8.50;10.0] 8.50 [6.25;10.0] 0.050 45
## A4 12.0 [11.0;12.0] 10.0 [9.50;12.0] 9.00 [8.00;11.0] 0.004 45
## A5 11.5 [11.0;12.8] 11.0 [10.0;11.5] 10.0 [9.00;11.2] 0.011 45
## B1 4.50 [3.25;6.00] 4.00 [3.50;6.00] 5.00 [4.75;6.00] 0.544 45
## A6 11.0 [10.2;12.0] 9.00 [8.00;11.0] 8.50 [6.75;9.25] 0.003 45
## A7 10.0 [9.25;11.8] 10.0 [7.50;10.5] 8.00 [6.75;9.00] 0.046 45
## Recog.A 15.0 [14.0;15.0] 14.0 [13.0;15.0] 14.5 [11.8;15.0] 0.238 45
## Recog.B 10.0 [8.00;11.5] 9.00 [7.50;10.0] 8.00 [6.00;10.0] 0.325 45
## Intrusion 1.00 [0.00;1.00] 1.00 [0.00;1.00] 0.00 [0.00;1.00] 0.632 45
## Perseverance 1.00 [1.00;1.00] 1.00 [1.00;1.00] 1.00 [0.75;1.00] 0.080 45
## Primacy 0.00 [0.00;1.00] 0.00 [0.00;0.50] 0.00 [0.00;0.25] 0.794 45
## Recency 0.00 [0.00;0.00] 0.00 [0.00;0.00] 0.00 [0.00;0.00] 0.793 45
## Total.RAVLT 51.0 [46.5;54.0] 44.0 [40.0;50.0] 41.5 [35.8;47.8] 0.035 45
## Forgetfulness.Rate 1.00 [0.90;1.00] 1.00 [0.85;1.05] 1.00 [0.88;1.30] 0.571 45
## Time.CW 122 [105;141] 141 [122;166] 136 [126;170] 0.101 45
## Time.C 116 [115;116] 116 [116;116] 116 [116;116] 0.866 45
## Digits.forward 8.00 [7.00;9.00] 7.00 [5.00;8.00] 6.00 [5.00;8.00] 0.023 45
## Digits.backward 6.50 [5.00;7.75] 6.00 [6.00;7.00] 5.00 [3.75;6.25] 0.278 45
## Span.forward 5.50 [5.00;6.00] 5.00 [4.00;5.00] 5.00 [4.00;5.25] 0.016 45
## Span.backward 4.00 [4.00;5.00] 3.00 [3.00;4.00] 3.50 [3.00;4.00] 0.032 45
## Corsi.forward 8.00 [7.00;9.00] 7.00 [6.00;7.00] 7.00 [6.00;8.25] 0.041 45
## Corsi.backward 6.00 [6.00;8.00] 5.00 [4.00;5.50] 5.00 [4.00;6.25] 0.011 45
## d2.RB 408 [390;446] 377 [291;458] 336 [299;398] 0.054 45
## d2.RL 400 [387;431] 368 [280;412] 318 [259;385] 0.017 45
## Reading.time 22.5 [20.2;24.5] 24.0 [20.5;26.5] 23.5 [21.5;26.8] 0.665 45
## Count.time 26.0 [23.5;29.8] 30.0 [27.5;32.0] 30.0 [27.5;31.2] 0.100 45
## Choice.time 38.0 [33.2;45.2] 50.0 [46.5;55.0] 46.5 [40.0;51.2] 0.003 45
## Alternation.time 49.5 [42.0;59.2] 61.0 [55.0;67.5] 62.5 [53.0;69.2] 0.006 45
## Inhibition 17.5 [12.2;20.8] 28.0 [23.0;32.5] 23.0 [19.0;29.0] 0.001 45
## Flexibility 27.5 [23.2;32.8] 38.0 [31.0;42.5] 39.0 [30.8;47.0] 0.002 45
## n_cat 3.00 [3.00;4.00] 3.00 [2.00;3.00] 3.00 [1.75;4.00] 0.280 45
## n_erro 7.00 [5.50;9.75] 9.00 [5.00;14.0] 10.0 [6.75;15.0] 0.295 45
## perda_set 0.00 [0.00;1.00] 0.00 [0.00;1.00] 0.00 [0.00;0.00] 0.162 45
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯Descritivas da Amostra
# Some variables are not important or had a very low variance
# perda_set, Primacy, Recency, Forgetfulness.Rate
BD <- red[,c(2,3,4,9:19,26,27,30:46)]
## CALCULATE ROBUST DESCRIPTIVE ANALYSIS ##
# TOTAL sample (all Types)
media <- round(sapply(BD[-3], function(i) tmean(i)), 2)
dp <- round(sapply(BD[-3], function(i) sd(i)), 2)
total <- cbind(media,dp)
total## media dp
## Age 15.33 1.19
## Education 10.85 1.35
## Vocabulary 41.59 8.73
## Matrix.Reasoning 24.07 4.98
## IQ 87.67 11.37
## A1 6.30 1.58
## A2 7.96 1.79
## A3 9.52 2.58
## A4 10.78 2.06
## A5 10.81 2.37
## B1 4.85 1.90
## A6 9.59 2.44
## A7 9.15 2.54
## Total.RAVLT 45.67 8.82
## Forgetfulness.Rate 0.97 0.18
## Digits.forward 6.96 2.18
## Digits.backward 5.93 2.27
## Span.forward 4.93 1.31
## Span.backward 3.70 1.17
## Corsi.forward 7.22 1.54
## Corsi.backward 5.33 1.98
## d2.RB 380.96 81.73
## d2.RL 362.81 84.73
## Reading.time 23.22 5.26
## Count.time 28.96 5.69
## Choice.time 45.78 11.67
## Alternation.time 58.63 13.45
## Inhibition 22.67 9.15
## Flexibility 34.52 11.68
## n_cat 2.93 1.32
## n_erro 8.93 4.73
## perda_set 0.07 0.71Descritivas dos Tipos
# ONCE
Once <- BD[which(BD$Type == "Once"),]
media <- round(sapply(Once[-3], function(i) tmean(i)), 2)
dp <- round(sapply(BD[-3], function(i) sd(i)), 2)
once <- cbind(media,dp)
# Multiple
Multiple <- BD[which(BD$Type == "Multiple"),]
media <- round(sapply(Multiple[-3], function(i) tmean(i)), 2)
dp <- round(sapply(BD[-3], function(i) sd(i)), 2)
multiple <- cbind(media,dp)
# Control
Control <- BD[which(BD$Type == "Control"),]
media <- round(sapply(Control[-3], function(i) tmean(i)), 2)
dp <- round(sapply(BD[-3], function(i) sd(i)), 2)
control <- cbind(media,dp)
cbind(once, multiple, control, total)## media dp media dp media dp media dp
## Age 14.80 1.19 15.22 1.19 16.20 1.19 15.33 1.19
## Education 10.30 1.35 10.78 1.35 11.30 1.35 10.85 1.35
## Vocabulary 41.10 8.73 36.89 8.73 47.10 8.73 41.59 8.73
## Matrix.Reasoning 23.00 4.98 20.89 4.98 27.70 4.98 24.07 4.98
## IQ 85.90 11.37 79.56 11.37 97.30 11.37 87.67 11.37
## A1 6.10 1.58 6.00 1.58 6.80 1.58 6.30 1.58
## A2 7.40 1.79 8.00 1.79 8.80 1.79 7.96 1.79
## A3 8.30 2.58 9.11 2.58 10.60 2.58 9.52 2.58
## A4 9.60 2.06 10.44 2.06 11.80 2.06 10.78 2.06
## A5 9.90 2.37 10.67 2.37 11.80 2.37 10.81 2.37
## B1 5.20 1.90 4.56 1.90 4.60 1.90 4.85 1.90
## A6 8.10 2.44 9.56 2.44 11.30 2.44 9.59 2.44
## A7 7.90 2.54 9.44 2.54 10.20 2.54 9.15 2.54
## Total.RAVLT 42.10 8.82 44.22 8.82 50.50 8.82 45.67 8.82
## Forgetfulness.Rate 1.03 0.18 0.97 0.18 0.95 0.18 0.97 0.18
## Digits.forward 6.40 2.18 6.56 2.18 8.20 2.18 6.96 2.18
## Digits.backward 5.10 2.27 6.22 2.27 6.30 2.27 5.93 2.27
## Span.forward 4.70 1.31 4.67 1.31 5.60 1.31 4.93 1.31
## Span.backward 3.50 1.17 3.33 1.17 4.40 1.17 3.70 1.17
## Corsi.forward 7.30 1.54 6.56 1.54 8.00 1.54 7.22 1.54
## Corsi.backward 4.90 1.98 4.89 1.98 6.70 1.98 5.33 1.98
## d2.RB 344.00 81.73 380.11 81.73 417.20 81.73 380.96 81.73
## d2.RL 323.70 84.73 355.00 84.73 408.30 84.73 362.81 84.73
## Reading.time 23.90 5.26 23.56 5.26 22.40 5.26 23.22 5.26
## Count.time 29.70 5.69 30.22 5.69 26.50 5.69 28.96 5.69
## Choice.time 46.30 11.67 50.78 11.67 39.00 11.67 45.78 11.67
## Alternation.time 61.70 13.45 61.67 13.45 50.10 13.45 58.63 13.45
## Inhibition 23.50 9.15 28.22 9.15 16.60 9.15 22.67 9.15
## Flexibility 38.50 11.68 37.67 11.68 27.80 11.68 34.52 11.68
## n_cat 2.80 1.32 2.56 1.32 3.30 1.32 2.93 1.32
## n_erro 10.40 4.73 9.44 4.73 7.70 4.73 8.93 4.73
## perda_set 0.00 0.71 0.22 0.71 0.30 0.71 0.07 0.71ANOVA robusta Tipos
# Robust one-way ANOVA (20% trimmed) among Types
type3.p <- round(sapply(red[,c(2,3,9:19,26,27,30:45)], function(i) t1way(i ~ red$Type)$p.value), 3)
# Effect Size (using Boostrap)
type3.EffSize <- round(sapply(red[,c(2,3,9:19,26,27,30:45)], function(i) t1waybt(i ~ red$Type)$Effect.Size), 3)
# Print results
cbind(type3.p, type3.EffSize)## type3.p type3.EffSize
## Age 0.081 0.371
## Education 0.178 0.403
## Vocabulary 0.004 0.574
## Matrix.Reasoning 0.001 0.639
## IQ 0.001 0.635
## A1 0.499 0.257
## A2 0.170 0.352
## A3 0.012 0.559
## A4 0.007 0.563
## A5 0.046 0.571
## B1 0.481 0.205
## A6 0.003 0.540
## A7 0.026 0.480
## Total.RAVLT 0.019 0.522
## Forgetfulness.Rate 0.688 0.244
## Digits.forward 0.081 0.531
## Digits.backward 0.288 0.341
## Span.forward 0.072 0.468
## Span.backward 0.004 0.445
## Corsi.forward 0.014 0.416
## Corsi.backward 0.046 0.593
## d2.RB 0.056 0.388
## d2.RL 0.036 0.472
## Reading.time 0.681 0.186
## Count.time 0.101 0.477
## Choice.time 0.007 0.567
## Alternation.time 0.031 0.610
## Inhibition 0.004 0.616
## Flexibility 0.007 0.569
## n_cat 0.190 0.295
## n_erro 0.318 0.274# YUEN robust t-test between Groups (Case N=31 vs Control N=14)
CaseControl.p <- round(sapply(red[,c(2,3,9:19,26,27,30:45)], function(i) yuen(i ~ red$Group)$p.value), 3)
# Effec size (with bootstrap), results may differ because of resampling
CaseControl.EffSize <- round(sapply(red[,c(2,3,9:19,26,27,30:45)], function(i) yuen.effect.ci(i ~ red$Group)$effsize), 3)
# Print results (Multiple vs Once)
cbind(CaseControl.p, CaseControl.EffSize)## CaseControl.p CaseControl.EffSize
## Age 0.011 0.466
## Education 0.130 0.369
## Vocabulary 0.004 0.598
## Matrix.Reasoning 0.000 0.743
## IQ 0.000 0.748
## A1 0.253 0.287
## A2 0.123 0.369
## A3 0.001 0.653
## A4 0.003 0.751
## A5 0.017 0.646
## B1 0.539 0.115
## A6 0.001 0.655
## A7 0.042 0.451
## Total.RAVLT 0.005 0.573
## Forgetfulness.Rate 0.554 0.165
## Digits.forward 0.025 0.639
## Digits.backward 0.429 0.201
## Span.forward 0.015 0.605
## Span.backward 0.001 0.515
## Corsi.forward 0.017 0.453
## Corsi.backward 0.012 0.604
## d2.RB 0.018 0.516
## d2.RL 0.007 0.576
## Reading.time 0.389 0.206
## Count.time 0.038 0.534
## Choice.time 0.005 0.643
## Alternation.time 0.009 0.629
## Inhibition 0.001 0.724
## Flexibility 0.001 0.739
## n_cat 0.164 0.317
## n_erro 0.136 0.365# Data without Control group
OnceMulti <- red[ which(red$Type !='Control'), ]
# YUEN robust t-test between Groups (Once N=15 vs Multiple N=16)
OnceMultiple.p <- round(sapply(OnceMulti[,c(2,3,9:19,26,27,30:45)], function(i) yuen(i ~ OnceMulti$Type)$p.value), 3)
# Effec size (with bootstrap), results may differ because of resampling
set.seed(7)
OnceMultiple.EffSize <- round(sapply(OnceMulti[,c(2,3,9:19,26,27,30:45)], function(i) yuen.effect.ci(i ~ OnceMulti$Type)$effsize), 3)
# Print results (Multiple vs Once)
cbind(OnceMultiple.p, OnceMultiple.EffSize)## OnceMultiple.p OnceMultiple.EffSize
## Age 0.520 0.174
## Education 0.396 0.294
## Vocabulary 0.181 0.332
## Matrix.Reasoning 0.298 0.289
## IQ 0.172 0.354
## A1 0.845 0.059
## A2 0.275 0.260
## A3 0.461 0.287
## A4 0.296 0.223
## A5 0.248 0.290
## B1 0.332 0.340
## A6 0.120 0.348
## A7 0.099 0.463
## Total.RAVLT 0.516 0.154
## Forgetfulness.Rate 0.532 0.244
## Digits.forward 0.843 0.039
## Digits.backward 0.125 0.426
## Span.forward 0.936 0.100
## Span.backward 0.595 0.100
## Corsi.forward 0.193 0.418
## Corsi.backward 0.986 0.061
## d2.RB 0.384 0.295
## d2.RL 0.412 0.238
## Reading.time 0.860 0.043
## Count.time 0.707 0.104
## Choice.time 0.169 0.354
## Alternation.time 0.993 0.060
## Inhibition 0.140 0.438
## Flexibility 0.828 0.052
## n_cat 0.658 0.121
## n_erro 0.688 0.110# Print ALL Robust results
cbind(type3.p, type3.EffSize, CaseControl.p, CaseControl.EffSize, OnceMultiple.p, OnceMultiple.EffSize)## type3.p type3.EffSize CaseControl.p CaseControl.EffSize
## Age 0.081 0.371 0.011 0.466
## Education 0.178 0.403 0.130 0.369
## Vocabulary 0.004 0.574 0.004 0.598
## Matrix.Reasoning 0.001 0.639 0.000 0.743
## IQ 0.001 0.635 0.000 0.748
## A1 0.499 0.257 0.253 0.287
## A2 0.170 0.352 0.123 0.369
## A3 0.012 0.559 0.001 0.653
## A4 0.007 0.563 0.003 0.751
## A5 0.046 0.571 0.017 0.646
## B1 0.481 0.205 0.539 0.115
## A6 0.003 0.540 0.001 0.655
## A7 0.026 0.480 0.042 0.451
## Total.RAVLT 0.019 0.522 0.005 0.573
## Forgetfulness.Rate 0.688 0.244 0.554 0.165
## Digits.forward 0.081 0.531 0.025 0.639
## Digits.backward 0.288 0.341 0.429 0.201
## Span.forward 0.072 0.468 0.015 0.605
## Span.backward 0.004 0.445 0.001 0.515
## Corsi.forward 0.014 0.416 0.017 0.453
## Corsi.backward 0.046 0.593 0.012 0.604
## d2.RB 0.056 0.388 0.018 0.516
## d2.RL 0.036 0.472 0.007 0.576
## Reading.time 0.681 0.186 0.389 0.206
## Count.time 0.101 0.477 0.038 0.534
## Choice.time 0.007 0.567 0.005 0.643
## Alternation.time 0.031 0.610 0.009 0.629
## Inhibition 0.004 0.616 0.001 0.724
## Flexibility 0.007 0.569 0.001 0.739
## n_cat 0.190 0.295 0.164 0.317
## n_erro 0.318 0.274 0.136 0.365
## OnceMultiple.p OnceMultiple.EffSize
## Age 0.520 0.174
## Education 0.396 0.294
## Vocabulary 0.181 0.332
## Matrix.Reasoning 0.298 0.289
## IQ 0.172 0.354
## A1 0.845 0.059
## A2 0.275 0.260
## A3 0.461 0.287
## A4 0.296 0.223
## A5 0.248 0.290
## B1 0.332 0.340
## A6 0.120 0.348
## A7 0.099 0.463
## Total.RAVLT 0.516 0.154
## Forgetfulness.Rate 0.532 0.244
## Digits.forward 0.843 0.039
## Digits.backward 0.125 0.426
## Span.forward 0.936 0.100
## Span.backward 0.595 0.100
## Corsi.forward 0.193 0.418
## Corsi.backward 0.986 0.061
## d2.RB 0.384 0.295
## d2.RL 0.412 0.238
## Reading.time 0.860 0.043
## Count.time 0.707 0.104
## Choice.time 0.169 0.354
## Alternation.time 0.993 0.060
## Inhibition 0.140 0.438
## Flexibility 0.828 0.052
## n_cat 0.658 0.121
## n_erro 0.688 0.110Pos-hoc Lincon
# pos-hoc LINCON method (20% trimmed one-way ANOVA)
type3.poshoc <- round(sapply(red[,c(2,3,9:19,26,27,30:45)], function(i) lincon(i ~ red$Type)$comp), 3)
# Select variables
testDF <- red[c(2,3,4,9:19,26,27,30:46)]
# Run LINCON pos-hoc with all variables
varListTest <- names(testDF)[-3]
#creates a model for each of the variables in question
model <- lapply(varListTest, function(x) {
WRS2::lincon(substitute(i ~ Type, list(i = as.name(x))), data = testDF)})
# Print results
model## [[1]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 0.97778 -0.37989 2.33545 0.14978
## Control vs. Once 1.40000 -0.29193 3.09193 0.13030
## Multiple vs. Once 0.42222 -1.28254 2.12699 0.52032
##
##
## [[2]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 0.52222 -0.87392 1.91836 0.39633
## Control vs. Once 1.00000 -0.31956 2.31956 0.18746
## Multiple vs. Once 0.47778 -0.97055 1.92611 0.39633
##
##
## [[3]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 10.21111 3.45344 16.96878 0.00292
## Control vs. Once 6.00000 -2.30302 14.30302 0.14807
## Multiple vs. Once -4.21111 -12.19795 3.77573 0.18058
##
##
## [[4]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 6.81111 2.66914 10.95308 0.00171
## Control vs. Once 4.70000 0.10883 9.29117 0.03099
## Multiple vs. Once -2.11111 -7.28771 3.06549 0.29751
##
##
## [[5]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 17.74444 8.19462 27.29427 0.00043
## Control vs. Once 11.40000 0.02507 22.77493 0.03453
## Multiple vs. Once -6.34444 -18.09840 5.40951 0.17222
##
##
## [[6]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 0.8 -0.97606 2.57606 0.64628
## Control vs. Once 0.7 -1.12269 2.52269 0.64628
## Multiple vs. Once -0.1 -1.43042 1.23042 0.84534
##
##
## [[7]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 0.8 -1.07203 2.67203 0.27534
## Control vs. Once 1.4 -0.47668 3.27668 0.19562
## Multiple vs. Once 0.6 -0.80232 2.00232 0.27534
##
##
## [[8]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 1.48889 0.22631 2.75147 0.01936
## Control vs. Once 2.30000 -0.63538 5.23538 0.10374
## Multiple vs. Once 0.81111 -2.13692 3.75914 0.46105
##
##
## [[9]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 1.35556 -0.34994 3.06105 0.09917
## Control vs. Once 2.20000 0.50059 3.89941 0.01111
## Multiple vs. Once 0.84444 -1.21709 2.90598 0.29561
##
##
## [[10]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 1.13333 -0.46533 2.73200 0.15795
## Control vs. Once 1.90000 0.07206 3.72794 0.04186
## Multiple vs. Once 0.76667 -0.92546 2.45879 0.24757
##
##
## [[11]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 0.04444 -1.89700 1.98589 0.95250
## Control vs. Once -0.60000 -2.16198 0.96198 0.66465
## Multiple vs. Once -0.64444 -2.38023 1.09134 0.66465
##
##
## [[12]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 1.74444 -0.23190 3.72079 0.06506
## Control vs. Once 3.20000 1.10197 5.29803 0.00289
## Multiple vs. Once 1.45556 -0.88607 3.79718 0.11991
##
##
## [[13]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 0.75556 -1.68104 3.19215 0.42284
## Control vs. Once 2.30000 0.29188 4.30812 0.02309
## Multiple vs. Once 1.54444 -0.80019 3.88908 0.19774
##
##
## [[14]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 6.27778 -0.67326 13.22882 0.05856
## Control vs. Once 8.40000 0.59664 16.20336 0.03468
## Multiple vs. Once 2.12222 -6.32025 10.56469 0.51634
##
##
## [[15]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple -0.01667 -0.18220 0.14886 0.78952
## Control vs. Once -0.08000 -0.32877 0.16877 0.78952
## Multiple vs. Once -0.06333 -0.32801 0.20135 0.78952
##
##
## [[16]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 1.64444 -0.52603 3.81492 0.12448
## Control vs. Once 1.80000 -0.25840 3.85840 0.10263
## Multiple vs. Once 0.15556 -1.88273 2.19385 0.84272
##
##
## [[17]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 0.07778 -1.68796 1.84351 0.90498
## Control vs. Once 1.20000 -1.09987 3.49987 0.37670
## Multiple vs. Once 1.12222 -0.75690 3.00134 0.37511
##
##
## [[18]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 0.93333 -0.08850 1.95517 0.08327
## Control vs. Once 0.90000 -0.31385 2.11385 0.13566
## Multiple vs. Once -0.03333 -1.11858 1.05191 0.93585
##
##
## [[19]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 1.06667 0.28199 1.85134 0.00706
## Control vs. Once 0.90000 0.14687 1.65313 0.01157
## Multiple vs. Once -0.16667 -0.97726 0.64393 0.59473
##
##
## [[20]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 1.44444 0.29462 2.59427 0.01315
## Control vs. Once 0.70000 -0.91668 2.31668 0.26920
## Multiple vs. Once -0.74444 -2.22310 0.73421 0.26920
##
##
## [[21]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 1.81111 -0.00692 3.62915 0.05373
## Control vs. Once 1.80000 -0.23423 3.83423 0.06477
## Multiple vs. Once -0.01111 -1.66643 1.64421 0.98599
##
##
## [[22]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 37.08889 -64.14305 138.3208 0.38427
## Control vs. Once 73.20000 0.36987 146.0301 0.05103
## Multiple vs. Once 36.11111 -71.74053 143.9627 0.38427
##
##
## [[23]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 53.3 -32.93203 139.5320 0.23552
## Control vs. Once 84.6 3.62130 165.5787 0.04121
## Multiple vs. Once 31.3 -66.86782 129.4678 0.41214
##
##
## [[24]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple -1.15556 -5.71453 3.40342 0.85978
## Control vs. Once -1.50000 -6.26549 3.26549 0.85978
## Multiple vs. Once -0.34444 -5.40331 4.71442 0.85978
##
##
## [[25]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple -3.72222 -8.09841 0.65396 0.11574
## Control vs. Once -3.20000 -7.53180 1.13180 0.13619
## Multiple vs. Once 0.52222 -3.08024 4.12469 0.70715
##
##
## [[26]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple -11.77778 -20.15869 -3.39687 0.00543
## Control vs. Once -7.30000 -16.40366 1.80366 0.09999
## Multiple vs. Once 4.47778 -3.74438 12.69994 0.16910
##
##
## [[27]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple -11.56667 -22.68064 -0.45269 0.04163
## Control vs. Once -11.60000 -23.59688 0.39688 0.04163
## Multiple vs. Once -0.03333 -10.59847 10.53180 0.99345
##
##
## [[28]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple -11.62222 -19.77296 -3.47148 0.00514
## Control vs. Once -6.90000 -13.54507 -0.25493 0.02805
## Multiple vs. Once 4.72222 -3.36527 12.80971 0.13986
##
##
## [[29]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple -9.86667 -18.09148 -1.64185 0.01612
## Control vs. Once -10.70000 -20.07386 -1.32614 0.01612
## Multiple vs. Once -0.83333 -10.76917 9.10250 0.82750
##
##
## [[30]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 0.74444 -0.26248 1.75137 0.20350
## Control vs. Once 0.50000 -1.03443 2.03443 0.65759
## Multiple vs. Once -0.24444 -1.71353 1.22464 0.65759
##
##
## [[31]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple -1.74444 -7.14248 3.65359 0.68820
## Control vs. Once -2.70000 -7.51585 2.11585 0.46315
## Multiple vs. Once -0.95556 -7.13620 5.22509 0.68820
##
##
## [[32]]
## Call:
## WRS2::lincon(formula = substitute(i ~ Type, list(i = as.name(x))),
## data = testDF)
##
## psihat ci.lower ci.upper p.value
## Control vs. Multiple 0.07778 -0.67914 0.83470 0.78932
## Control vs. Once 0.30000 -0.24616 0.84616 0.44062
## Multiple vs. Once 0.22222 -0.41467 0.85911 0.66382Correlacoes
# Robust correlations
cor.rob <- pball(testDF[c(1,2,4,7,14,17,18,21,22,23,29,30:33)])
psych::cor.plot(cor.rob$pbcorm)