This document contains the output for a series of models using beta regression to analyze the data from Danvers and Hu’s honesty study.

library(brms)
## Warning: package 'brms' was built under R version 3.4.4
## Loading required package: Rcpp
## Warning: package 'Rcpp' was built under R version 3.4.4
## Loading required package: ggplot2
## Loading 'brms' package (version 2.2.0). Useful instructions
## can be found by typing help('brms'). A more detailed introduction
## to the package is available through vignette('brms_overview').
## Run theme_set(theme_default()) to use the default bayesplot theme.
# load data
hdat.l <- read.csv("~/Dropbox/Honesty_Project/Judging Honesty Studies/honesty_social_issues/hdat_social_long.csv")

# scaling the honesty data to 0-1 interval
hdat.l[,c(3:11)] <- hdat.l[,c(3:11)]/100

# remove 0 & 1 from all outcome variables
hdat.l[,3:11] <- apply(hdat.l[,3:11], 2, function(x) ifelse(x == 1.0, 0.99,ifelse(x == 0, 0.01, x)))

# listwise deletion
hdat.lC <- na.omit(hdat.l)

Models

Honesty of Statement

# estimating the model with specific narrative and order as covariates
bcpriors <- get_prior(belief ~ condPos*nar*order + (1|ResponseId), data=hdat.lC, family="beta")

stmt.fitc <- brm(belief ~ condPos*nar*order + (1|ResponseId), data=hdat.lC, family="beta",
                prior = bcpriors)
## Compiling the C++ model
## Start sampling
## 
## SAMPLING FOR MODEL 'beta brms-model' NOW (CHAIN 1).
## 
## Gradient evaluation took 0.001288 seconds
## 1000 transitions using 10 leapfrog steps per transition would take 12.88 seconds.
## Adjust your expectations accordingly!
## 
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##  Elapsed Time: 84.0125 seconds (Warm-up)
##                91.3264 seconds (Sampling)
##                175.339 seconds (Total)
## 
## 
## SAMPLING FOR MODEL 'beta brms-model' NOW (CHAIN 2).
## 
## Gradient evaluation took 0.001109 seconds
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## Adjust your expectations accordingly!
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##  Elapsed Time: 86.9757 seconds (Warm-up)
##                81.8506 seconds (Sampling)
##                168.826 seconds (Total)
## 
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## SAMPLING FOR MODEL 'beta brms-model' NOW (CHAIN 3).
## 
## Gradient evaluation took 0.001775 seconds
## 1000 transitions using 10 leapfrog steps per transition would take 17.75 seconds.
## Adjust your expectations accordingly!
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##  Elapsed Time: 89.2537 seconds (Warm-up)
##                87.2505 seconds (Sampling)
##                176.504 seconds (Total)
## 
## 
## SAMPLING FOR MODEL 'beta brms-model' NOW (CHAIN 4).
## 
## Gradient evaluation took 0.001275 seconds
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## Adjust your expectations accordingly!
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##  Elapsed Time: 89.3075 seconds (Warm-up)
##                86.7083 seconds (Sampling)
##                176.016 seconds (Total)
print(summary(stmt.fitc))
##  Family: beta 
##   Links: mu = logit; phi = identity 
## Formula: belief ~ condPos * nar * order + (1 | ResponseId) 
##    Data: hdat.lC (Number of observations: 2253) 
## Samples: 4 chains, each with iter = 2000; warmup = 1000; thin = 1; 
##          total post-warmup samples = 4000
##     ICs: LOO = NA; WAIC = NA; R2 = NA
##  
## Group-Level Effects: 
## ~ResponseId (Number of levels: 757) 
##               Estimate Est.Error l-95% CI u-95% CI Eff.Sample Rhat
## sd(Intercept)     0.87      0.03     0.80     0.94       1427 1.00
## 
## Population-Level Effects: 
##                                Estimate Est.Error l-95% CI u-95% CI
## Intercept                          0.28      0.14     0.00     0.56
## condPos                            1.34      0.21     0.92     1.75
## narhomosexuality                  -0.28      0.20    -0.66     0.10
## narrace                            0.02      0.21    -0.39     0.42
## order                             -0.10      0.06    -0.23     0.02
## condPos:narhomosexuality           0.57      0.30    -0.03     1.15
## condPos:narrace                   -0.09      0.30    -0.68     0.49
## condPos:order                      0.07      0.10    -0.12     0.26
## narhomosexuality:order             0.12      0.09    -0.06     0.30
## narrace:order                     -0.06      0.10    -0.25     0.13
## condPos:narhomosexuality:order    -0.18      0.14    -0.46     0.09
## condPos:narrace:order              0.11      0.14    -0.15     0.38
##                                Eff.Sample Rhat
## Intercept                            1975 1.00
## condPos                              1792 1.00
## narhomosexuality                     2390 1.00
## narrace                              2126 1.00
## order                                1920 1.00
## condPos:narhomosexuality             2200 1.00
## condPos:narrace                      2048 1.00
## condPos:order                        1752 1.00
## narhomosexuality:order               2405 1.00
## narrace:order                        2100 1.00
## condPos:narhomosexuality:order       2188 1.00
## condPos:narrace:order                1988 1.00
## 
## Family Specific Parameters: 
##     Estimate Est.Error l-95% CI u-95% CI Eff.Sample Rhat
## phi     4.39      0.18     4.05     4.74       4000 1.00
## 
## Samples were drawn using sampling(NUTS). For each parameter, Eff.Sample 
## is a crude measure of effective sample size, and Rhat is the potential 
## scale reduction factor on split chains (at convergence, Rhat = 1).
plot(stmt.fitc)