ETHBE: Online Survey on "Exams and Written Papers"

In GLMMRR: Generalized Linear Mixed Model (GLMM) for Binary Randomized Response Data

Online Survey on "Exams and Written Papers"

Description

The goal of the survey was to estimate the prevalence of various forms of student misconduct such as plagiarizing or cheating in exams. Because students might be reluctant to reveal information on such behaviors, special techniques for sensitive questions were employed in addition to direct questioning. Respondents were randomly assigned to direct questioning or one of five different sensitive question techniques. The dataset contains the (randomized or direct) responses from 4281 students of the University of Bern and ETH Zurich. Each row holds the response to one question for one respondent. The variables are as follows:

Usage

data(ETHBE)

Format

A data frame in long format with 21405 rows and 29 variables

Details

• id. Identification code of the respondent

• RR_response. Binary randomized or direct response

• Question. Which question was asked

• expcond. Experimental condition

• protect. Level of respondent protection

• subgroup. Subgroups for balanced assignment to experimental conditions

• sample. Sample group

• survey duration. Total time to complete survey (in seconds)

• mobile. Respondent used mobile device (at start of interview)

• java. Javascript version (at start of interview)

• age_cat. Year of birth category

• gender. Gender

• misconduct. Sum score of five binary items on student misconduct

• misconduct2. String of responses to five binary items on student misconduct

• field. Major field of study

• education. Type of study program

• semester. Current semester

• working. Working next to studying

• germanlang. German language skills

• riskattitude. Risk attitude (GSOEP 11-point scale)

• gpa. Current grade point average

• pressure. Studying is a lot of pressure

• stressed. Feeling very stressed in exams

• exams. Number of exams taken

• numberpapers. Number of papers handed in

• RRmodel. Randomized Response Model

• p1. Randomized Response parameter p1

• p2. Randomized Response parameter p2

Author(s)

Marc Hoeglinger, Ben Jann and Andreas Diekmann

References

https://ideas.repec.org/p/bss/wpaper/8.html

GLMMRR documentation built on Nov. 5, 2025, 6:20 p.m.