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Unobserved heterogeneity between individuals in Group-Focused Enmity

Friehs, M.-T.; Masselmann, J.; Trautner, M.; Kotzur, P.F.; Schmidt, P.

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M.-T. Friehs

J. Masselmann

M. Trautner

P. Schmidt


Group-focused enmity (GFE) and related research have mostly focused on variable-centred analyses such as structural equation modelling and factor analysis, implicitly assuming that the results apply uniformly to all participants in the sample. Person-centred research questions and analysis methods, which investigate unobserved heterogeneity in the sample, have been lacking in GFE research. Nonetheless, initial evidence exists from research on Islamophobia and GFE that various unobserved latent classes (i.e., subgroups) differing in their average prejudice can be identified within one dataset. In this manuscript, we applied factor mixture modelling to investigate unobserved heterogeneity using the data of the German GFE survey 2011. We found two latent classes of equivalent factor-analytical composition with consistently high versus low expressions of target-specific prejudice. No comparison of latent GFE means was possible. Membership in the high prejudice latent class was associated with higher age, right-wing political orientation, high right-wing authoritarianism and high social dominance orientation. Our findings demonstrate the importance of exploring unobserved heterogeneity in attitudes research and outline how person-centred research can complement variable-centred research in order to understand social-psychological phenomena.


Friehs, M., Masselmann, J., Trautner, M., Kotzur, P., & Schmidt, P. (2022). Unobserved heterogeneity between individuals in Group-Focused Enmity. International journal of conflict and violence, 16, 1-17.

Journal Article Type Article
Online Publication Date Apr 13, 2022
Publication Date 2022
Deposit Date Apr 13, 2022
Publicly Available Date Apr 19, 2022
Journal International Journal of Conflict and Violence
Publisher IJCV
Peer Reviewed Peer Reviewed
Volume 16
Pages 1-17


Published Journal Article (506 Kb)

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Copyright Statement
Copyright (c) 2022 Maria-Therese Friehs, Judith Masselmann, Maike Trautner, Patrick Ferdinand Kotzur, Peter Schmidt

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

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