Dataset of Integrated Measures of Religion (DIM-R). Harmonization of religiosity data from selected international multiwave surveys

Abstract

ABSTRACT This article presents the Dataset of Integrated Measures of Religion (DIM-R), explains how it was constructed, and outlines its potential for helping to address long-standing research questions in the social scientific study of religion. DIM-R integrates four variables often used to measure religious commitment: self-declared religiosity, religious attendance, prayer, and affiliation/denominational affiliation. These variables are harmonized in four repeated cross-sectional international surveys: European Social Survey, International Social Survey Programme, European Values Study and World Values Survey. Harmonization enables cross-country and over-time comparisons in religiosity leveraging multiple data sources. Unlike the variables in the original datasets, which have different scaling and response options, DIM-R transforms them to a consistent categorization and scaling. The DIM-R dataset can assist social scientists of religion by reducing the data cleaning burden associated with integrating multiple datasets, and by increasing the statistical weight of observations across countries, time, and cohorts. To validate the DIM-R dataset, we present the exact harmonization process and examine the reliability and consistency of our analytic subset of the combined data using linear mixed models.