---
title: "RESPONDENTS’ PREFERRED SURVEY TOPICS: MEASUREMENT AND PREVALENCE"
subtitle: "Replication Files: Study 2"
author: "Tobias Gummer, Saskia Bartholomäus, and Bernd Weiss"
date: "19.01.2026"
output:
  html_document:
    theme: united
    toc: true
    toc_depth: 4
    toc_float:
      collapsed: true
      smooth_scroll: true
---

```{css, echo=FALSE}
#TOC {
  alignment-baseline: central
}

h1.title{
  font-size: 20px
}

h1 {
  font-size: 18px
}

h2, h3 {
  font-size: 16px
}

h4 {
  font-size: 14px
}

img {
  margin-top: 0 !important;
  margin-bottom: 0 !important;
  margin-right: auto !important;
  margin-left: 0 !important;
  padding: 10px;
}

pre {
  border: 0;
  background-color: rgb(0 0 0 / 1%); 
  color: #808080;
  max-height: 300px;
  overflow-y: auto;
}
    
.tocify {
  border: 0;
  border-radius: 0;
  box-sizing: 0
}
    
.container-fluid {
  margin-right: 0;
  margin-left: 0;
  padding-left: 50px;
  padding-right: 50px
  width: 100%
}

.main-container {
  padding-top: 20px;
  width: 100%
}

div.main-container {
    max-width: 100%;
}
    
.list-group-item.active, .list-group-item.active:hover, .list-group-item.active:focus {
  z-index: 2;
  color: #dd4814;
  background-color: #ffffff;
  border-color: #fff;
}

.hljs-keyword {
  color: #dd4814;
  font-weight: bold;
}

.hljs-string {
  color: #dd4814;
}

.hljs-literal {
  color: #dd4814;
}

/* custom scrollbar */
::-webkit-scrollbar {
  width: 20px;
  border: none; 
}

::-webkit-scrollbar-track {
  background-color: transparent;
}

::-webkit-scrollbar-thumb {
  background-color: #999;
  border-radius: 20px;
  border: 6px solid transparent;
  background-clip: content-box;
}

::-webkit-scrollbar-thumb:hover {
  background-color: #808080;
}

div[style*="border: 1px solid #ddd"] {
    border: none !important;  /* Remove the border */
    padding: 0px !important;
    overflow-y: scroll !important;
    height: 300px !important;
    overflow-x: scroll !important;
    width: 100% !important;
}
```

```{r setup, include=FALSE, cache = FALSE}
require("knitr")
#knitr::opts_chunk$set(echo = TRUE, fig.align='center')
knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file())
```

# Introduction 

Gummer, Tobias, Bartholomäus, Saskia, and Weiss, Bernd (2026): "Respondents’ Preferred Survey Topics: Measurement and Prevalence." Survey Research Methods.

Respondents’ interest in a survey’s topic is used frequently by survey researchers to explain and predict survey errors. Whether respondents are interested in a survey’s content relates to their participation and cognitive answering processes, which consequently impacts nonresponse and measurement errors. Since the content of a survey is under the control of the researchers who design and conduct it, the content could be varied to improve participation and answering behavior. Unfortunately, research is lacking as to (i) how to measure these preferences, (ii) whether groups of respondents differ in their topic preferences, and (iii) the topic preferences in the social science survey samples. We have addressed this research gap by presenting the findings of three experimental studies that we conducted. In our study, we validated a measurement instrument to assess respondents’ topic interests. Moreover, we found that topic preferences varied between samples and respondent subgroups. However, across samples we consistently found that respondents were more interested in answering questions on personal rather than political topics. Based on our empirical findings, we provide practical recommendations for survey research and outline future research opportunities.  

The ReplicationFileStudy2.html contains all analyses of study 2 reported in the cited article. The published R.Rmd files allow users to replicate the results. To access the data set required for replication, a data use agreement is necessary. To reproduce the analyses, please follow these steps:

1. Place all R.Rmd files in a subfolder named scripts and the data set in a subfolder named data. 
2. Required R packages are listed and loaded in 01am_pop.Rmd. Please review this file to ensure that all necessary packages are installed before proceeding. Note that running 01am_pop.Rmd will automatically create all required subfolders for the workflow.
3. For the file 02dp_pop.Rmd, include the path to required data set in the first code chunk.
4. After making any necessary adjustments, you only need to run 05re_pop.Rmd. This file will source all other scripts and reproduce the analyses and results as described in the project.

GESIS – Leibniz Institute for the Social Sciences (2024). GESIS Panel - Standard Edition (ZA5665; Version 54.0.0) [Data set]. https://doi.org/10.4232/1.14386 

```{r clearing memory, message=FALSE, warning=FALSE, include=FALSE, results='hide'}
# Clearing Memory
rm(list = ls(all.names = TRUE)) 
gc()                            
```
```{r chunk duplicates, message=FALSE, warning=FALSE, include=FALSE, results='hide'}
# Allow Chunk Label Duplicates 
options(knitr.duplicate.label = "allow")
```
```{r getting directory, message=FALSE, warning=FALSE, include=FALSE}
# Getting Directory
getwd()
folders <- c("scripts", "data", "graphs", "html")
for (f in folders) if (!dir.exists(f)) dir.create(f, recursive = TRUE)
```
```{r installing packages, include=FALSE}
# Installing Packages if required
cat('install.packages(c( "sjPlot", "ggplot2", "lmtest", "sandwich", "estimatr", "ggeffects", "Hmisc", "broom", "tidyr", "plyr", "marginaleffects", "kableExtra", "purrr", "dplyr", "psych", "sjlabelled", "vtable", "devtools", "ggpubr", "gtools", "lme4", "gmodels", "haven"))\n')

cat("if (!requireNamespace('remotes', quietly = TRUE)) install.packages('remotes')
remotes::install_github('rkabacoff/qacDR')\n")
```
```{r loading packages, message=FALSE, warning=FALSE, include=FALSE}
# Loading Packages
library(sjPlot)
library(ggplot2)
library(lmtest)
library(sandwich)
library(estimatr)
library(ggeffects)
library(Hmisc)
library(broom)
library(tidyr)
library(plyr)
library(marginaleffects)
library(kableExtra)
library(purrr)
library(dplyr)
library(haven)
library(psych)
library(sjlabelled)
library(qacDR)
library(vtable)
library(devtools)
library(ggpubr)
library(gtools)
library(lme4)
library(gmodels)
```
```{r set seed, message=FALSE, warning=FALSE}
# Random Number Generation
set.seed(42)
```
```{r graph theme, include=FALSE}
# Set Custom Theme
custom_theme <- theme(legend.position = "top", 
 legend.title=element_blank(), 
 panel.grid = element_line(linetype = 3, linewidth = 0.5, color = "gray"),
 panel.border = element_blank(),
 title = element_text(size = 10, margin = NULL, family = "Times New Roman"),
 axis.line = element_line(colour = "gray"),
 axis.title = element_text(size = 10, family = "Times New Roman", face = "plain"),
 axis.text.y = element_text(size = 10, margin = margin(5, 5, 5, 10), family = "Times New Roman", colour = "black"),
 axis.text.x = element_text(size = 10, margin = margin(5, 5, 0, 5), family = "Times New Roman", colour = "black"),
 legend.text = element_text(size = 10, margin = NULL, family = "Times New Roman"),
 plot.title = element_text(hjust = 0.5), 
 plot.caption = element_text(size = 10, family = "Times New Roman", face = "italic", colour = "gray", hjust = 0),
 plot.caption.position = "plot")
```

```{r preparation, child = 'scripts/02dp_pop.Rmd'}
```
```{r descriptives, child = 'scripts/03ds_pop.Rmd'}
```
```{r pcanalysis, child = 'scripts/04fa_pop.Rmd'}
```

# Documentation

```{r session info, message=FALSE, warning=FALSE}
session_info()
```

