Replication Data for: An Ordinal Item Response Model for Understanding Attitudes.

Loading...
Thumbnail Image

Files

README.txt (778 B)

Description: Readme

Replication.R (32.32 KB)

Description: Replication file

Data.RData (127.75 KB)

Description: Dataset

Identifiers

Publication date

Reading date

Authors

Mauerer, Ingrid Doris
Tutz, Gerhard

Collaborators

Advisors

Tutors

Editors

Journal Title

Journal ISSN

Volume Title

Publisher

Harvard Dataverse

Metrics

Google Scholar

Share

Research Projects

Organizational Units

Journal Issue

Department/Institute

Referenced by

Mauerer, Ingrid and Tutz, Gerhard, An Ordinal Item Response Model for Understanding Attitudes (November 03, 2025). This is the accepted version of the manuscript: Mauerer, I. & Tutz, G. (2025). "An Ordinal Item Response Model for Understanding Attitudes". Forthcoming Sociological Methods and Research. doi: 10.1177/00491241251403078, Available at SSRN: https://ssrn.com/abstract=4977675 or http://dx.doi.org/10.2139/ssrn.4977675

Abstract

Is supplement to: Mauerer, I. & Tutz, G. (2025). "An Ordinal Item Response Model for Understanding Attitudes". Forthcoming Sociological Methods and Research. doi: 10.1177/00491241251403078 Open Access
We present an item response model for ordinal public opinion data to understand individual-level variation in attitudes as a function of covariates. The approach allows investigating how individuals (or population subgroups) differ in substantive stances and attitude strength. It is a two-dimensional partial credit model that incorporates covariates linked to attitude direction and strength into the basic model. We exemplify the types of substantive insights into heterogeneity that can be obtained from the approach but not from existing models with two applications: attitudes toward gender equality (European Values Study) and the evaluation of presidential candidates (American National Election Study).

Description

Bibliographic citation

Mauerer, Ingrid; Tutz, Gerhard, 2025, "Replication Data for: An Ordinal Item Response Model for Understanding Attitudes", https://doi.org/10.7910/DVN/CZJJAF, Harvard Dataverse, V1

Endorsement

Review

Supplemented By

Referenced by