Cross-Cultural Measurement Invariance Among German Migrants

Monday, 16 July 2018: 16:42
Oral Presentation
Jonas BESTE, Institute of Employment Research, Germany
An emphasis of many surveys is the measuring of subjective indicators concerning a wide field of topics. The measurement instruments used for these purposes (e. g. batteries of multiple items) rely on the assumption of measurement invariance. This means, that all respondents have a similar understanding of the measured underlying construct as well as each individual item. To compare means of different groups of respondents we must ensure that these groups understand and respond to the questions in similar ways. Otherwise comparison between groups can lead to incorrect conclusions.
Previous methodological research has shown that measurement invariance is not given for all instruments and groups. Particularly, differences appear between groups of different cultural background (Davidov et al., 2014). Therefore testing measuring invariance is of utmost importance for surveys including respondents with cultural diversity.
The Panel Study “Labour Market and Social Security” (PASS) is an ongoing yearly household panel study of German welfare benefits recipients and is concerned with their living conditions, socio-economic situation and the dynamics of welfare receipt. Culturally the PASS respondents are very heterogeneous due to the large proportion of individuals with a migration background. This is intensified by the rising number of refugees from Syria, Iraq and Afghanistan over the last years, which enter the study through annual refreshment samples.
The recent developments and their socio-political implications increase the need for valid sociological insights. To assure comparability between groups of different cultural background we test multiple measurement instruments for multiple subjective indicators in PASS (e. g. self-efficacy, gender role, psychometric measures) using a multi-group CFA framework (see Vandenberg & Lance 2000). We operationalize cultural background using questions on migration background, spoken language, religion and nationality.