BF Penguin confirmatory

Data preparation

Required R libraries

#rm(list = ls())

library(dplyr, quietly = TRUE)
library(BayesFactor, quietly = TRUE)
set.seed(123)

Loading the dataset

setwd(dir = "/Users/ivanropovik/OneDrive/MANUSCRIPTS/2017 penguin project_sexual orientation/Datasets")
full.data <- read.csv(file = "penguin_confirm.csv", header = TRUE, sep = ";")
#View(full.data)
data.na <- full.data %>% select(DEQ, csi, cbt, seconds, urald, sinod, sex, romrec, sexpref, Zmonog)

Listwise deletion

data <- data.na[complete.cases(data.na),]

Dichotomizing the sexpref variable

data$sexpref10[data$sexpref == 1] <- 1
data$sexpref10[data$sexpref == 2] <- 2
data$sexpref10[data$sexpref == 3] <- 2
data$sexpref10[data$sexpref == 4] <- 2

Calculation of interaction terms

data <- data %>% mutate(
  int_rom_alpha = DEQ * romrec,
  int_rom_beta = csi * romrec,
  int_sexpref_alpha = DEQ * sexpref10,
  int_sexpref_beta = csi * sexpref10,
  int_monog_alpha = DEQ * Zmonog,
  int_monog_beta = csi * Zmonog,
  int_sex_alpha = DEQ * sex,
  int_sex_beta = csi * sex,
  int_sex_rom_alphaXW = DEQ * romrec,
  int_sex_rom_alphaXZ = DEQ * sex,
  int_sex_rom_alphaWZ = romrec * sex,
  int_sex_rom_alphaXWZ = DEQ * romrec * sex
)

BF options

Prior width (r scale)

r.scale <- sqrt(2)/4

Number of iterations

n.iter <- 100000

CSI mediation

Alpha path

bfmodel1 <- regressionBF(csi ~ DEQ + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
alpha.path <- bfmodel1[31]/bfmodel1[30]

BF for the alpha path

paste(ifelse(extractBF(alpha.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(alpha.path)$bf > 1, extractBF(alpha.path)$bf, 1/extractBF(alpha.path)$bf), 2), sep = "")

## [1] "BF10 = 509.8"

Bayesian posterior estimate of the alpha path

round(summary(posterior(alpha.path, iterations =  n.iter))$statistics[1], 3)

## [1] 0.013

Posterior probability of the alpha path

post.odds.alpha <- newPriorOdds(alpha.path) * alpha.path
round(extractProbabilities(as.BFprobability(post.odds.alpha)[1])$probs, 3)

## [1] 0.998

Beta path

bfmodel2 <- regressionBF(cbt ~ csi + DEQ + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
beta.path <- bfmodel2[63]/bfmodel2[62]

BF for the beta path

paste(ifelse(extractBF(beta.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(beta.path)$bf > 1, extractBF(beta.path)$bf, 1/extractBF(beta.path)$bf), 2), sep = "")

## [1] "BF10 = 43.23"

Bayesian posterior estimate of the beta path

round(summary(posterior(beta.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.046

Posterior probability of the beta path

post.odds.beta <- newPriorOdds(beta.path) * beta.path
round(extractProbabilities(as.BFprobability(post.odds.beta)[1])$probs, 3)

## [1] 0.977

Tau path

tau.path <- bfmodel2[63]/bfmodel2[61]

BF for the tau path

paste(ifelse(extractBF(tau.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(tau.path)$bf > 1, extractBF(tau.path)$bf, 1/extractBF(tau.path)$bf), 2), sep = "")

## [1] "BF10 = 623.04"

Bayesian posterior estimate of the tau path

round(summary(posterior(tau.path, iterations = n.iter))$statistic[2], 3)

## [1] -0.005

Posterior probability of the tau path

post.odds.tau <- newPriorOdds(tau.path) * tau.path
round(extractProbabilities(as.BFprobability(post.odds.tau)[1])$probs, 3)

## [1] 0.998

BF for the mediation - the indirect (ab) path

post.prob.med <- extractBF(alpha.path)$bf/(extractBF(alpha.path)$bf + 1) * extractBF(beta.path)$bf/(extractBF(beta.path)$bf + 1)
bf.med <- post.prob.med/(1 - post.prob.med)

paste(ifelse(bf.med > 1, "BF10 = ", "BF01 = "), round(ifelse(bf.med > 1, bf.med, 1/bf.med), 2), sep = "")

## [1] "BF10 = 39.78"

Romantic - moderated CSI mediation

Moderation of the alpha path

bfmodel1rom <- regressionBF(csi ~ DEQ + romrec + int_rom_alpha + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
alpha.rom <- bfmodel1rom[127]/bfmodel1rom[124]

BF for the moderation of the alpha path

paste(ifelse(extractBF(alpha.rom)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(alpha.rom)$bf > 1, extractBF(alpha.rom)$bf, 1/extractBF(alpha.rom)$bf), 2), sep = "")

## [1] "BF10 = 429.78"

Bayesian posterior estimate of the moderation effect of the alpha path

round(summary(posterior(alpha.rom, iterations = n.iter))$statistics[1], 3)

## [1] 0.01

Posterior probability for the moderation effect of the alpha path

post.odds.alpha.rom <- newPriorOdds(alpha.rom) * alpha.rom
round(extractProbabilities(as.BFprobability(post.odds.alpha.rom)[1])$probs, 3)

## [1] 0.998

Moderation of the beta path

bfmodel2rom <- regressionBF(cbt ~ csi + DEQ + romrec + int_rom_beta + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
beta.rom <- bfmodel2rom[255]/bfmodel2rom[251]

BF for the moderation of the beta path

paste(ifelse(extractBF(beta.rom)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(beta.rom)$bf > 1, extractBF(beta.rom)$bf, 1/extractBF(beta.rom)$bf), 2), sep = "")

## [1] "BF01 = 3.42"

Bayesian posterior estimate of the moderation effect of the beta path

round(summary(posterior(beta.rom, iterations = n.iter))$statistic[1], 3)

## [1] 0.04

Posterior probability for the moderation effect of the beta path

post.odds.beta.rom <- newPriorOdds(beta.rom) * beta.rom
round(extractProbabilities(as.BFprobability(post.odds.beta.rom)[1])$probs, 3)

## [1] 0.226

Sexual orientation - moderated CSI mediation

Moderation of the alpha path

bfmodel1sexpref <- regressionBF(csi ~ DEQ + sexpref10 + int_sexpref_alpha + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
alpha.sexpref <- bfmodel1sexpref[127]/bfmodel1sexpref[124]

BF for the moderation of the alpha path

paste(ifelse(extractBF(alpha.sexpref)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(alpha.sexpref)$bf > 1, extractBF(alpha.sexpref)$bf, 1/extractBF(alpha.sexpref)$bf), 2), sep = "")

## [1] "BF01 = 2.57"

Bayesian posterior estimate of the moderation effect of the alpha path

round(summary(posterior(alpha.sexpref, iterations =  n.iter))$statistics[1], 3)

## [1] 0.031

Posterior probability for the moderation effect of the alpha path

post.odds.alpha.sexpref <- newPriorOdds(alpha.sexpref) * alpha.sexpref
round(extractProbabilities(as.BFprobability(post.odds.alpha.sexpref)[1])$probs, 3)

## [1] 0.28

Moderation of the beta path

bfmodel2sexpref <- regressionBF(cbt ~ csi + DEQ + sexpref10 + int_sexpref_beta + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
beta.sexpref <- bfmodel2sexpref[255]/bfmodel2sexpref[251]

BF for the moderation of the beta path

paste(ifelse(extractBF(beta.sexpref)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(beta.sexpref)$bf > 1, extractBF(beta.sexpref)$bf, 1/extractBF(beta.sexpref)$bf), 2), sep = "")

## [1] "BF01 = 3.81"

Bayesian posterior estimate of the moderation effect of the beta path

round(summary(posterior(beta.sexpref, iterations = n.iter))$statistic[1], 3)

## [1] 0.002

Posterior probability for the moderation effect of the beta path

post.odds.beta.sexpref <- newPriorOdds(beta.sexpref) * beta.sexpref
round(extractProbabilities(as.BFprobability(post.odds.beta.sexpref)[1])$probs, 3)

## [1] 0.208

Monogamy - moderated CSI mediation

Moderation of the alpha path

bfmodel1monog <- regressionBF(csi ~ DEQ + Zmonog + int_monog_alpha + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
alpha.monog <- bfmodel1monog[127]/bfmodel1monog[124]

BF for the moderation of the alpha path

paste(ifelse(extractBF(alpha.monog)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(alpha.monog)$bf > 1, extractBF(alpha.monog)$bf, 1/extractBF(alpha.monog)$bf), 2), sep = "")

## [1] "BF01 = 2.79"

Bayesian posterior estimate of the moderation effect of the alpha path

round(summary(posterior(alpha.monog, iterations =  n.iter))$statistics[1], 3)

## [1] 0.013

Posterior probability for the moderation effect of the alpha path

post.odds.alpha.monog <- newPriorOdds(alpha.monog) * alpha.monog
round(extractProbabilities(as.BFprobability(post.odds.alpha.monog)[1])$probs, 3)

## [1] 0.264

Moderation of the beta path

bfmodel2monog <- regressionBF(cbt ~ csi + DEQ + Zmonog + int_monog_beta + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
beta.monog <- bfmodel2monog[255]/bfmodel2monog[251]

BF for the moderation of the beta path

paste(ifelse(extractBF(beta.monog)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(beta.monog)$bf > 1, extractBF(beta.monog)$bf, 1/extractBF(beta.monog)$bf), 2), sep = "")

## [1] "BF01 = 4.39"

Bayesian posterior estimate of the moderation effect of the beta path

round(summary(posterior(beta.monog, iterations = n.iter))$statistic[1], 3)

## [1] 0.045

Posterior probability for the moderation effect of the beta path

post.odds.beta.monog <- newPriorOdds(beta.monog) * beta.monog
round(extractProbabilities(as.BFprobability(post.odds.beta.monog)[1])$probs, 3)

## [1] 0.186

Monogamy mediation

Alpha path

bfmodel1 <- regressionBF(Zmonog ~ DEQ + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
alpha.path <- bfmodel1[31]/bfmodel1[30]

BF for the alpha path

paste(ifelse(extractBF(alpha.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(alpha.path)$bf > 1, extractBF(alpha.path)$bf, 1/extractBF(alpha.path)$bf), 2), sep = "")

## [1] "BF10 = 2.73"

Bayesian posterior estimate of the alpha path

round(summary(posterior(alpha.path, iterations =  n.iter))$statistics[1], 3)

## [1] 0.006

Posterior probability of the alpha path

post.odds.alpha <- newPriorOdds(alpha.path) * alpha.path
round(extractProbabilities(as.BFprobability(post.odds.alpha)[1])$probs, 3)

## [1] 0.732

Beta path

bfmodel2 <- regressionBF(cbt ~ Zmonog + DEQ + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
beta.path <- bfmodel2[63]/bfmodel2[62]

BF for the beta path

paste(ifelse(extractBF(beta.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(beta.path)$bf > 1, extractBF(beta.path)$bf, 1/extractBF(beta.path)$bf), 2), sep = "")

## [1] "BF01 = 4.74"

Bayesian posterior estimate of the beta path

round(summary(posterior(beta.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.012

Posterior probability of the beta path

post.odds.beta <- newPriorOdds(beta.path) * beta.path
round(extractProbabilities(as.BFprobability(post.odds.beta)[1])$probs, 3)

## [1] 0.174

Tau path

tau.path <- bfmodel2[63]/bfmodel2[61]

BF for the tau path

paste(ifelse(extractBF(tau.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(tau.path)$bf > 1, extractBF(tau.path)$bf, 1/extractBF(tau.path)$bf), 2), sep = "")

## [1] "BF10 = 112.65"

Bayesian posterior estimate of the tau path

round(summary(posterior(tau.path, iterations = n.iter))$statistic[2], 3)

## [1] -0.004

Posterior probability of the tau path

post.odds.tau <- newPriorOdds(tau.path) * tau.path
round(extractProbabilities(as.BFprobability(post.odds.tau)[1])$probs, 3)

## [1] 0.991

BF for the mediation - the indirect (ab) path

post.prob.med <- extractBF(alpha.path)$bf/(extractBF(alpha.path)$bf + 1) * extractBF(beta.path)$bf/(extractBF(beta.path)$bf + 1)
bf.med <- post.prob.med/(1 - post.prob.med)

paste(ifelse(bf.med > 1, "BF10 = ", "BF01 = "), round(ifelse(bf.med > 1, bf.med, 1/bf.med), 2), sep = "")

## [1] "BF01 = 6.84"

MON->CSI double mediation

DEQ_CBT path

bfmodel1 <- regressionBF(cbt ~ DEQ + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
DEQ_CBT.path <- bfmodel1[31]/bfmodel1[30]

BF for the DEQ_CBT path

paste(ifelse(extractBF(DEQ_CBT.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(DEQ_CBT.path)$bf > 1, extractBF(DEQ_CBT.path)$bf, 1/extractBF(DEQ_CBT.path)$bf), 2), sep = "")

## [1] "BF10 = 87.26"

Bayesian posterior estimate of the DEQ_CBT path

round(summary(posterior(DEQ_CBT.path, iterations =  n.iter))$statistics[1], 3)

## [1] -0.004

Posterior probability of the DEQ_CBT path

post.odds.DEQ_CBT <- newPriorOdds(DEQ_CBT.path) * DEQ_CBT.path
round(extractProbabilities(as.BFprobability(post.odds.DEQ_CBT)[1])$probs, 3)

## [1] 0.989

DEQ_MON path

bfmodel2 <- regressionBF(Zmonog ~ DEQ + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
DEQ_MON.path <- bfmodel2[31]/bfmodel2[30]

BF for the DEQ_MON path

paste(ifelse(extractBF(DEQ_MON.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(DEQ_MON.path)$bf > 1, extractBF(DEQ_MON.path)$bf, 1/extractBF(DEQ_MON.path)$bf), 2), sep = "")

## [1] "BF10 = 2.73"

Bayesian posterior estimate of the DEQ_MON path

round(summary(posterior(DEQ_MON.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.006

Posterior probability of the DEQ_MON path

post.odds.DEQ_MON <- newPriorOdds(DEQ_MON.path) * DEQ_MON.path
round(extractProbabilities(as.BFprobability(post.odds.DEQ_MON)[1])$probs, 3)

## [1] 0.732

DEQ_CSI path

bfmodel3 <- regressionBF(csi ~ DEQ + Zmonog + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
DEQ_CSI.path <- bfmodel3[63]/bfmodel3[62]

BF for the DEQ_CSI path

paste(ifelse(extractBF(DEQ_CSI.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(DEQ_CSI.path)$bf > 1, extractBF(DEQ_CSI.path)$bf, 1/extractBF(DEQ_CSI.path)$bf), 2), sep = "")

## [1] "BF10 = 295.92"

Bayesian posterior estimate of the DEQ_CSI path

round(summary(posterior(DEQ_CSI.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.012

Posterior probability of the DEQ_CSI path

post.odds.DEQ_CSI <- newPriorOdds(DEQ_CSI.path) * DEQ_CSI.path
round(extractProbabilities(as.BFprobability(post.odds.DEQ_CSI)[1])$probs, 3)

## [1] 0.997

MON_CSI path

bfmodel4 <- regressionBF(csi ~ Zmonog + DEQ + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
MON_CSI.path <- bfmodel4[63]/bfmodel4[62]

BF for the MON_CSI path

paste(ifelse(extractBF(MON_CSI.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(MON_CSI.path)$bf > 1, extractBF(MON_CSI.path)$bf, 1/extractBF(MON_CSI.path)$bf), 2), sep = "")

## [1] "BF01 = 2.04"

Bayesian posterior estimate of the MON_CSI path

round(summary(posterior(MON_CSI.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.07

Posterior probability of the MON_CSI path

post.odds.MON_CSI <- newPriorOdds(MON_CSI.path) * MON_CSI.path
round(extractProbabilities(as.BFprobability(post.odds.MON_CSI)[1])$probs, 3)

## [1] 0.329

MON_CBT path

bfmodel5 <- regressionBF(cbt ~ Zmonog + DEQ + csi + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
MON_CBT.path <- bfmodel5[127]/bfmodel5[126]

BF for the MON_CBT path

paste(ifelse(extractBF(MON_CBT.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(MON_CBT.path)$bf > 1, extractBF(MON_CBT.path)$bf, 1/extractBF(MON_CBT.path)$bf), 2), sep = "")

## [1] "BF01 = 5.14"

Bayesian posterior estimate of the MON_CBT path

round(summary(posterior(MON_CBT.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.009

Posterior probability of the MON_CBT path

post.odds.MON_CBT <- newPriorOdds(MON_CBT.path) * MON_CBT.path
round(extractProbabilities(as.BFprobability(post.odds.MON_CBT)[1])$probs, 3)

## [1] 0.163

CSI_CBT path

bfmodel6 <- regressionBF(cbt ~ csi + DEQ + Zmonog + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
CSI_CBT.path <- bfmodel6[127]/bfmodel6[126]

BF for the CSI_CBT path

paste(ifelse(extractBF(CSI_CBT.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(CSI_CBT.path)$bf > 1, extractBF(CSI_CBT.path)$bf, 1/extractBF(CSI_CBT.path)$bf), 2), sep = "")

## [1] "BF10 = 39.87"

Bayesian posterior estimate of the CSI_CBT path

round(summary(posterior(CSI_CBT.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.045

Posterior probability of the CSI_CBT path

post.odds.CSI_CBT <- newPriorOdds(CSI_CBT.path) * CSI_CBT.path
round(extractProbabilities(as.BFprobability(post.odds.CSI_CBT)[1])$probs, 3)

## [1] 0.976

CSI->MON double mediation

DEQ_CBT path

bfmodel1 <- regressionBF(cbt ~ DEQ + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
DEQ_CBT.path <- bfmodel1[31]/bfmodel1[30]

BF for the DEQ_CBT path

paste(ifelse(extractBF(DEQ_CBT.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(DEQ_CBT.path)$bf > 1, extractBF(DEQ_CBT.path)$bf, 1/extractBF(DEQ_CBT.path)$bf), 2), sep = "")

## [1] "BF10 = 87.26"

Bayesian posterior estimate of the DEQ_CBT path

round(summary(posterior(DEQ_CBT.path, iterations =  n.iter))$statistics[1], 3)

## [1] -0.004

Posterior probability of the DEQ_CBT path

post.odds.DEQ_CBT <- newPriorOdds(DEQ_CBT.path) * DEQ_CBT.path
round(extractProbabilities(as.BFprobability(post.odds.DEQ_CBT)[1])$probs, 3)

## [1] 0.989

DEQ_CSI path

bfmodel2 <- regressionBF(csi ~ DEQ + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
DEQ_CSI.path <- bfmodel2[31]/bfmodel2[30]

BF for the DEQ_CSI path

paste(ifelse(extractBF(DEQ_CSI.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(DEQ_CSI.path)$bf > 1, extractBF(DEQ_CSI.path)$bf, 1/extractBF(DEQ_CSI.path)$bf), 2), sep = "")

## [1] "BF10 = 509.8"

Bayesian posterior estimate of the DEQ_CSI path

round(summary(posterior(DEQ_CSI.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.013

Posterior probability of the DEQ_CSI path

post.odds.DEQ_CSI <- newPriorOdds(DEQ_CSI.path) * DEQ_CSI.path
round(extractProbabilities(as.BFprobability(post.odds.DEQ_CSI)[1])$probs, 3)

## [1] 0.998

DEQ_MON path

bfmodel3 <- regressionBF(Zmonog ~ DEQ + csi + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
DEQ_MON.path <- bfmodel3[63]/bfmodel3[62]

BF for the DEQ_MON path

paste(ifelse(extractBF(DEQ_MON.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(DEQ_MON.path)$bf > 1, extractBF(DEQ_MON.path)$bf, 1/extractBF(DEQ_MON.path)$bf), 2), sep = "")

## [1] "BF10 = 1.61"

Bayesian posterior estimate of the DEQ_MON path

round(summary(posterior(DEQ_MON.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.005

Posterior probability of the DEQ_MON path

post.odds.DEQ_MON <- newPriorOdds(DEQ_MON.path) * DEQ_MON.path
round(extractProbabilities(as.BFprobability(post.odds.DEQ_MON)[1])$probs, 3)

## [1] 0.618

CSI_MON path

bfmodel4 <- regressionBF(Zmonog ~ csi + DEQ + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
CSI_MON.path <- bfmodel4[63]/bfmodel4[62]

BF for the CSI_MON path

paste(ifelse(extractBF(CSI_MON.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(CSI_MON.path)$bf > 1, extractBF(CSI_MON.path)$bf, 1/extractBF(CSI_MON.path)$bf), 2), sep = "")

## [1] "BF01 = 1.34"

Bayesian posterior estimate of the CSI_MON path

round(summary(posterior(CSI_MON.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.051

Posterior probability of the CSI_MON path

post.odds.CSI_MON <- newPriorOdds(CSI_MON.path) * CSI_MON.path
round(extractProbabilities(as.BFprobability(post.odds.CSI_MON)[1])$probs, 3)

## [1] 0.427

CSI_CBT path

bfmodel5 <- regressionBF(cbt ~ csi + DEQ + Zmonog + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
CSI_CBT.path <- bfmodel5[127]/bfmodel5[126]

BF for the CSI_CBT path

paste(ifelse(extractBF(CSI_CBT.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(CSI_CBT.path)$bf > 1, extractBF(CSI_CBT.path)$bf, 1/extractBF(CSI_CBT.path)$bf), 2), sep = "")

## [1] "BF10 = 39.87"

Bayesian posterior estimate of the CSI_CBT path

round(summary(posterior(CSI_CBT.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.045

Posterior probability of the CSI_CBT path

post.odds.CSI_CBT <- newPriorOdds(CSI_CBT.path) * CSI_CBT.path
round(extractProbabilities(as.BFprobability(post.odds.CSI_CBT)[1])$probs, 3)

## [1] 0.976

MON_CBT path

bfmodel6 <- regressionBF(cbt ~ Zmonog + DEQ + csi + seconds + urald + sinod + sex, data, rscaleCont = r.scale)
MON_CBT.path <- bfmodel6[127]/bfmodel6[126]

BF for the MON_CBT path

paste(ifelse(extractBF(MON_CBT.path)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(MON_CBT.path)$bf > 1, extractBF(MON_CBT.path)$bf, 1/extractBF(MON_CBT.path)$bf), 2), sep = "")

## [1] "BF01 = 5.14"

Bayesian posterior estimate of the MON_CBT path

round(summary(posterior(MON_CBT.path, iterations = n.iter))$statistic[1], 3)

## [1] 0.009

Posterior probability of the MON_CBT path

post.odds.MON_CBT <- newPriorOdds(MON_CBT.path) * MON_CBT.path
round(extractProbabilities(as.BFprobability(post.odds.MON_CBT)[1])$probs, 3)

## [1] 0.163

Sex - moderated CSI mediation

Moderation of the alpha path

bfmodel1sex <- regressionBF(csi ~ DEQ + sex + int_sex_alpha + seconds + urald + sinod, data, rscaleCont = r.scale)
alpha.sex <- bfmodel1sex[63]/bfmodel1sex[60]

BF for the moderation of the alpha path

paste(ifelse(extractBF(alpha.sex)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(alpha.sex)$bf > 1, extractBF(alpha.sex)$bf, 1/extractBF(alpha.sex)$bf), 2), sep = "")

## [1] "BF10 = 1.59"

Bayesian posterior estimate of the moderation effect of the alpha path

round(summary(posterior(alpha.sex, iterations = n.iter))$statistics[1], 3)

## [1] -0.012

Posterior probability for the moderation effect of the alpha path

post.odds.alpha.sex <- newPriorOdds(alpha.sex) * alpha.sex
round(extractProbabilities(as.BFprobability(post.odds.alpha.sex)[1])$probs, 3)

## [1] 0.614

Moderation of the beta path

bfmodel2sex <- regressionBF(cbt ~ csi + DEQ + sex + int_sex_beta + seconds + urald + sinod, data, rscaleCont = r.scale)
beta.sex <- bfmodel2sex[127]/bfmodel2sex[123]

BF for the moderation of the beta path

paste(ifelse(extractBF(beta.sex)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(beta.sex)$bf > 1, extractBF(beta.sex)$bf, 1/extractBF(beta.sex)$bf), 2), sep = "")

## [1] "BF01 = 5.94"

Bayesian posterior estimate of the moderation effect of the beta path

round(summary(posterior(beta.sex, iterations = n.iter))$statistic[1], 3)

## [1] 0.04

Posterior probability for the moderation effect of the beta path

post.odds.beta.sex <- newPriorOdds(beta.sex) * beta.sex
round(extractProbabilities(as.BFprobability(post.odds.beta.sex)[1])$probs, 3)

## [1] 0.144

Sex - moderated moderation (by romantic) of the CSI mediation (M11)

Moderated moderation of the alpha path

bfmodel1sex_rom <- regressionBF(csi ~ DEQ + romrec + sex + int_sex_rom_alphaXW + int_sex_rom_alphaXZ + int_sex_rom_alphaWZ + int_sex_rom_alphaXWZ + seconds + urald + sinod, data, rscaleCont = r.scale)
alpha.3way <- bfmodel1sex_rom[1023]/bfmodel1sex_rom[1016]

BF for the moderation of the alpha path

paste(ifelse(extractBF(alpha.3way)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(alpha.3way)$bf > 1, extractBF(alpha.3way)$bf, 1/extractBF(alpha.3way)$bf), 2), sep = "")

## [1] "BF01 = 3.05"

Bayesian posterior estimate of the moderation effect of the alpha path

round(summary(posterior(alpha.3way, iterations = n.iter))$statistics[1], 3)

## [1] -0.016

Posterior probability for the moderation effect of the alpha path

post.odds.alpha.3way <- newPriorOdds(alpha.3way) * alpha.3way
round(extractProbabilities(as.BFprobability(post.odds.alpha.3way)[1])$probs, 3)

## [1] 0.247

Sex - moderated CSI mediation controlling for romantic

Moderation of the alpha path

bfmodel1sex_rom <- regressionBF(csi ~ DEQ + sex + int_sex_alpha + romrec + seconds + urald + sinod, data, rscaleCont = r.scale)
alpha.sex <- bfmodel1sex_rom[127]/bfmodel1sex_rom[124]

BF for the moderation of the alpha path

paste(ifelse(extractBF(alpha.sex)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(alpha.sex)$bf > 1, extractBF(alpha.sex)$bf, 1/extractBF(alpha.sex)$bf), 2), sep = "")

## [1] "BF10 = 1.75"

Bayesian posterior estimate of the moderation effect of the alpha path

round(summary(posterior(alpha.sex, iterations = n.iter))$statistics[1], 3)

## [1] -0.013

Posterior probability for the moderation effect of the alpha path

post.odds.alpha.sex <- newPriorOdds(alpha.sex) * alpha.sex
round(extractProbabilities(as.BFprobability(post.odds.alpha.sex)[1])$probs, 3)

## [1] 0.637

Moderation of the beta path

bfmodel2sex_rom <- regressionBF(cbt ~ csi + DEQ + sex + int_sex_beta + romrec + seconds + urald + sinod, data, rscaleCont = r.scale)
beta.sex <- bfmodel2sex_rom[255]/bfmodel2sex_rom[251]

BF for the moderation of the beta path

paste(ifelse(extractBF(beta.sex)$bf > 1, "BF10 = ", "BF01 = "),
      round(ifelse(extractBF(beta.sex)$bf > 1, extractBF(beta.sex)$bf, 1/extractBF(beta.sex)$bf), 2), sep = "")

## [1] "BF01 = 5.52"

Bayesian posterior estimate of the moderation effect of the beta path

round(summary(posterior(beta.sex, iterations = n.iter))$statistic[1], 3)

## [1] 0.036

Posterior probability for the moderation effect of the beta path

post.odds.beta.sex <- newPriorOdds(beta.sex) * beta.sex
round(extractProbabilities(as.BFprobability(post.odds.beta.sex)[1])$probs, 3)

## [1] 0.153

sessionInfo()

## R version 3.3.2 (2016-10-31)
## Platform: x86_64-apple-darwin13.4.0 (64-bit)
## Running under: macOS Sierra 10.12.6
## 
## locale:
## [1] sk_SK.UTF-8/sk_SK.UTF-8/sk_SK.UTF-8/C/sk_SK.UTF-8/sk_SK.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] BayesFactor_0.9.12-2 Matrix_1.2-8         coda_0.19-1         
## [4] dplyr_0.5.0         
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_0.12.10       knitr_1.15.1       magrittr_1.5      
##  [4] lattice_0.20-34    R6_2.2.0           pbapply_1.3-2     
##  [7] stringr_1.2.0      tools_3.3.2        parallel_3.3.2    
## [10] grid_3.3.2         DBI_0.6            htmltools_0.3.5   
## [13] MatrixModels_0.4-1 gtools_3.5.0       yaml_2.1.14       
## [16] lazyeval_0.2.0     assertthat_0.1     rprojroot_1.2     
## [19] digest_0.6.12      tibble_1.2         evaluate_0.10     
## [22] rmarkdown_1.3      stringi_1.1.2      backports_1.0.5   
## [25] mvtnorm_1.0-6

BF Penguin confirmatory

Ivan Ropovik

Thu Jun 8 22:53:34 2017

Data preparation

Required R libraries

Loading the dataset

Listwise deletion

Dichotomizing the sexpref variable

Calculation of interaction terms

BF options

Prior width (r scale)

Number of iterations

CSI mediation

Alpha path

Beta path

Tau path

BF for the mediation - the indirect (ab) path

Romantic - moderated CSI mediation

Moderation of the alpha path

Moderation of the beta path

Sexual orientation - moderated CSI mediation

Moderation of the alpha path

Moderation of the beta path

Monogamy - moderated CSI mediation

Moderation of the alpha path

Moderation of the beta path

Monogamy mediation

Alpha path

Beta path

Tau path

BF for the mediation - the indirect (ab) path

MON->CSI double mediation

DEQ_CBT path

DEQ_MON path

DEQ_CSI path

MON_CSI path

MON_CBT path

CSI_CBT path

CSI->MON double mediation

DEQ_CBT path

DEQ_CSI path

DEQ_MON path

CSI_MON path

CSI_CBT path

MON_CBT path

Sex - moderated CSI mediation

Moderation of the alpha path

Moderation of the beta path

Sex - moderated moderation (by romantic) of the CSI mediation (M11)

Moderated moderation of the alpha path

Sex - moderated CSI mediation controlling for romantic

Moderation of the alpha path

Moderation of the beta path