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@incollection{ Kern2016, title = {Effect Comparison in Multilevel Structural Equation Models with Non-Metric Outcomes}, author = {Kern, Christoph and Stein, Petra}, year = {2016}, booktitle = {JSM 2016 Proceedings, Social Statistics Section}, pages = {3892-3901}, address = {Alexandria, VA}, publisher = {American Statistical Association}, urn = {https://nbn-resolving.org/urn:nbn:de:0168-ssoar-50108-5}, abstract = {This study discusses difficulties of effect comparisons in multilevel structural equation models with non-metric outcomes, such as nonlinear dyadic mixed-effects regression. In these models, the fixation of the level-1 error variances induces substantial drawbacks in the context of effect comparisons which align with the well-known problems of standard single- and multilevel nonlinear models. Specifically, the level-1 and level-2 coefficients as well as the level-2 variance components are implicitly rescaled by the amount of unobserved level-1 residual variation and thus may apparently differ across (and within) equations despite of true effect equality. Against this background, the present study discusses a multilevel extension of the method proposed by Sobel and Arminger (1992) with which potential differences in level-1 residual variation can be taken into account through the specification of non-linear parameter constraints. The problems of effect comparisons in multilevel probit SEM's and the proposed correction method are exemplified with a simulation study.}, keywords = {statistical analysis; simulation; statistische Analyse; statistische Methode; statistical method; Simulation; Mehrebenenanalyse; empirical social research; multi-level analysis; multivariate Analyse; Modellvergleich; model comparison; multivariate analysis; empirische Sozialforschung}}