Bennink,MargotCroon,M.A.Vermunt,J.K.2025-02-012025-02-012015Bennink, M, Croon, M A & Vermunt, J K 2015, 'Stepwise latent class models for explaining group-level putcomes using discrete individual-level predictors', Multivariate Behavioral Research, vol. 50, no. 6, pp. 662-675. https://doi.org/10.1080/00273171.2015.10748790027-3171ORCID: /0000-0001-9053-9330/work/10605381110.1080/00273171.2015.1074879https://hdl.handle.net/20.500.14602/64417Explaining group-level outcomes from individual-level predictors requires aggregating the individual-level scores to the group level and correcting the group-level estimates for measurement errors in the aggregated scores. However, for discrete variables it is not clear how to perform the aggregation and correction. It is shown how stepwise latent class analysis can be used to do this. First, a latent class model is estimated in which the scores on a discrete individual-level predictor are used to construct group-level latent classes. Second, this latent class model is used to aggregate the individual-level predictor by assigning the groups to the latent classes. Third, a group-level analysis is performed in which the aggregated measures are related to the remaining group-level variables while correcting for the measurement error in the class assignments. This stepwise approach is introduced in a multilevel mediation model with a single individual-level mediator, and compared to existing methods in a simulation study. We also show how a mediation model with multiple group-level latent variables can be used with multiple individual-level mediators and this model is applied to explain team productivity (group level) as a function of job control (individual level), job satisfaction (individual level), and enriched job design (group level). Keywords: latent class analysis, micro-macro analysis, multilevel analysis, discrete variables, stepwise modelingenginfo:eu-repo/semantics/restrictedAccessStepwise latent class models for explaining group-level putcomes using discrete individual-level predictorsArticleGeneral rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. - Users may download and print one copy of any publication from the public portal for the purpose of private study or research. - You may not further distribute the material or use it for any profit-making activity or commercial gain - You may freely distribute the URL identifying the publication in the public portal" Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.9271364https://research.tilburguniversity.edu/en/publications/1002fa8d-bb82-4d32-ac55-d428246b8dcb(c) Universiteit van TilburgBennink, MargotCroon, M.A.Vermunt, J.K.ยง0000-0001-9053-9330