In marton-balazs-kovacs/trolleyMultilabReplication: Analyses for the PSA006 Moral Thinking Across the World Multilab Replication Project

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
) 

set.seed(42)

# Load packages
devtools::load_all()
# library(trolleyMultilabReplication)
library(tidyverse)
library(kableExtra)
library(gt)
library(countrycode)

# Save data for each study separately
study1a <- dplyr::filter(trolley, include_study1a)
study1b <- dplyr::filter(trolley, include_study1b)
study2a <- dplyr::filter(trolley, include_study2a)
study2b <- dplyr::filter(trolley, include_study2b)
intention_a <- dplyr::filter(trolley, include_study1a|include_study2a)
intention_b <- dplyr::filter(trolley, include_study1b|include_study2b)

# Save data but without the familiarity filter for each study
study1a_nf <- dplyr::filter(trolley, include_study1a_withoutfamiliarity)
study1b_nf <- dplyr::filter(trolley, include_study1b_withoutfamiliarity)
study2a_nf <- dplyr::filter(trolley, include_study2a_withoutfamiliarity)
study2b_nf <- dplyr::filter(trolley, include_study2b_withoutfamiliarity)
intention_a_nf <- dplyr::filter(trolley, include_study1a_withoutfamiliarity|include_study2a_withoutfamiliarity)
intention_b_nf <- dplyr::filter(trolley, include_study1b_withoutfamiliarity|include_study2b_withoutfamiliarity)

# Save data but with only those who failed the familiar exclusion criteria
study1a_f <- dplyr::filter(trolley, include_study1a_familiar)
study1b_f <- dplyr::filter(trolley, include_study1b_familiar)
study2a_f <- dplyr::filter(trolley, include_study2a_familiar)
study2b_f <- dplyr::filter(trolley, include_study2b_familiar)

# Add individualism and collectivism scales
study2a <- add_ind_col_scale(study2a)
study2b <- add_ind_col_scale(study2b)
study2a_nf <- add_ind_col_scale(study2a_nf)
study2b_nf <- add_ind_col_scale(study2b_nf)

# Add individualism and collectivism scales
trolley <- add_ind_col_scale(trolley)

2. Main replication analysis

Study 2a and 2b

rscale <-  0.26
vars1a <- c("trolley_3_rate", "trolley_2_rate")

studys1a_results <- 
  bind_rows(
    calculate_intention_stat(intention_a, vars = vars1a, 
                             label = "Exclusion", rscale = rscale),
    calculate_intention_stat(intention_a_nf, vars = vars1a, 
                             label = "Include familiar", rscale = rscale),
    calculate_intention_stat(trolley, vars = vars1a, 
                             label = "No exclusion", rscale = rscale)) %>% 
  mutate(p = ifelse(as.numeric(p) < .001, "<.001", round(as.numeric(p),3)))

kbl(
  studys1a_results,
  format = "latex",
  col.names = c("Exclusion", "Cluster", "BF",  "t", "df", "p", "Cohen's d", "Raw effect", "$89\\%$ CI"),
  booktabs = T,
  escape = F,
  caption = "The effect of intention on moral dilemma judgements on Trolley dilemmas",
  centering = T,
  position = "H") %>%
  kable_styling( full_width = F,  position = "left", latex_options = "scale_down") %>%
  row_spec(row = 0, bold = TRUE) %>%
  collapse_rows(columns = 1, valign = "top", latex_hline = "major", row_group_label_position = "identity")

rscale <-  0.26
vars1b <- c("speedboat_3_rate", "speedboat_2_rate")

studys1b_results <- 
  bind_rows(
    calculate_intention_stat(intention_b, vars = vars1b, 
                             label = "Exclusion", rscale = rscale),
    calculate_intention_stat(intention_b_nf, vars = vars1b, 
                             label = "Include familiar", rscale = rscale),
    calculate_intention_stat(trolley, vars = vars1b, 
                             label = "No exclusion", rscale = rscale)) %>% 
  mutate(p = ifelse(as.numeric(p) < .001, "<.001", round(as.numeric(p),3)))

kbl(
  studys1b_results,
  format = "latex",
  col.names = c("Exclusion", "Cluster", "BF",  "t", "df", "p", "Cohen's d", "Raw effect", "$89\\%$ CI"),
  booktabs = T,
  escape = F,
  caption = "The effect of intention on moral dilemma judgements on Speedboat dilemmas",
  centering = T,
  position = "H") %>%
  kable_styling( full_width = F,  position = "left", latex_options = "scale_down") %>%
  row_spec(row = 0, bold = TRUE) %>%
  collapse_rows(columns = 1, valign = "top", latex_hline = "major", row_group_label_position = "identity")

# Set parameters for analysis
rscale <- .26
vars1a <- c("trolley_1_rate", "trolley_2_rate")

# Running the analysis
studys1a_results <- 
  bind_rows(
    calculate_study1_stat(study1a, vars = vars1a, 
                          label = "Exclusion", rscale = rscale), 
    calculate_study1_stat(study1a_nf, vars = vars1a, 
                          label = "Including familiar", rscale = rscale)) %>% 
  mutate(
    # RR was calculated by manual iteration
    RR = c("7.00e-03, 14.00", "<1.00e-05, 2.80e+06", "1.20e-02, 4.30", "1.50e-05, 6.50e+03", "<1.00e-05, 5.50e+11", "<1.00e-05, 2.90e+04"),
    # Changing the formatting of small p-values
    p = ifelse(as.numeric(p) < .001, "<.001", round(as.numeric(p),3)), 
    Dilemma = rep("Trolley", 6))%>%
  select(Dilemma, everything())

rscale <- .26
vars1b <- c("speedboat_1_rate", "speedboat_2_rate")

studys1b_results <-
  bind_rows(
    calculate_study1_stat(study1b, vars = vars1b,
                          label = "Exclusion", rscale = rscale),
    calculate_study1_stat(study1b_nf, vars = vars1b,
                          label = "Including familiar", rscale = rscale)) %>%
  # RR was calculated by manual iteration
  mutate(
    RR = c("1.80e-05, 1.70e+04", "1.30e-03, 74.00", "3.30e-02, 1.20", "6.0e-05, 1.70e+03", "<1.00e-05, 5.5e+05", "<1.00e-05, 4.0e+06"),

    p = ifelse(as.numeric(p) < .001, "<.001", round(as.numeric(p),3)),
    Dilemma = rep("Speedboat", 6))%>%
  select(Dilemma, everything())

study1_all = rbind(studys1a_results, studys1b_results)

kbl(
  study1_all,
  format = "latex",
  col.names = c("Dilemma", "Exclusion", "Cluster", "BF", "RR", "t", "df", "p", "Cohen's d", "Raw effect", "$89\\%$ CI"),
  booktabs = TRUE,
  escape = F,
  caption = "The effect of personal force on moral dilemma judgements on Trolley and Speedboat dilemmas",
  centering = TRUE,
  position = "H") %>%
  kable_styling(full_width = FALSE, position = "left", latex_options = "scale_down") %>%
  row_spec(row = 0, bold = TRUE) %>%
  collapse_rows(columns = 1, valign = "middle", latex_hline = "major", row_group_label_position = "identity")%>%
  collapse_rows(columns = 2, valign = "top", latex_hline = "linespace",
                row_group_label_position = "identity")

rscaleFixed <- c("personal_force:intention" = 0.19)
vars2a <- c("trolley_3_rate", "trolley_4_rate", "trolley_5_rate", "trolley_6_rate")

studys2a_results <-
  bind_rows(
    calculate_study2_stat(study2a, vars = vars2a,
                          label = "Exclusion", rscaleFixed = rscaleFixed),
    calculate_study2_stat(study2a_nf, vars = vars2a,
                          label = "Include familiar", rscaleFixed = rscaleFixed)) %>%
  # RR was calculated by manual iteration
  mutate(
    RR = c(c("0.022, 0.64", "0.0275, 0.2", "0.000058, 1.80e+03", "2.50e-02, 1.35", "0.00223, 60", "<1.00e-05, 3700000000")),
    p = ifelse(as.numeric(p) < .001, "<.001", round(as.numeric(p),3)), 
    Dilemma = rep("Trolley", 6))%>%
  select(Dilemma, everything())

rscaleFixed <- c("personal_force:intention" = 0.19)
vars2b <- c("speedboat_3_rate", "speedboat_4_rate", "speedboat_5_rate", "speedboat_6_rate")

studys2b_results <-
  bind_rows(
    calculate_study2_stat(study2b, vars = vars2b,
                          label = "Exclusion", rscaleFixed=rscaleFixed),
    calculate_study2_stat(study2b_nf, vars = vars2b,
                          label = "Include familiar", rscaleFixed=rscaleFixed)) %>%
  # RR was calculated by manual iteration
  mutate(
    RR = c("0.046, 0.69", "5.10e-02, 0.65", "3.60e-02, 1.15", "0.045, 0.6", "0.032, 0.94", "0.0006, 75"),
    p = ifelse(as.numeric(p) < .001, "<.001", round(as.numeric(p),3)),
    Dilemma = rep("Speedboat", 6))%>%
  select(Dilemma, everything())

study2_all = rbind(studys2a_results, studys2b_results)

kbl(
  study2_all,
  format = "latex",
  col.names = c("Dilemma", "Exclusion", "Cluster", "BF", "RR", "b", "$89\\%$ CI", "p", 'Partial $\\eta^2$', "Raw effect"),
  booktabs = T,
  escape = F,
  caption = "Do personal force interact with intention on Speedboat and Trolley dilemmas?",
  centering = T,
  position = "H") %>%
  kable_styling(full_width = F,  position="left", latex_options = "scale_down") %>%
  row_spec(row = 0, bold = TRUE) %>%
  collapse_rows(columns = 1, valign = "middle", latex_hline = "major", row_group_label_position = "identity")%>%
  collapse_rows(columns = 2, valign = "top", latex_hline = "linespace",
                row_group_label_position = "identity")

marton-balazs-kovacs/trolleyMultilabReplication documentation built on Oct. 13, 2023, 3:15 p.m.