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Alexander Robitzsch; Oliver Lüdtke – Structural Equation Modeling: A Multidisciplinary Journal, 2025
The random intercept cross-lagged panel model (RICLPM) decomposes longitudinal associations between two processes X and Y into stable between-person associations and temporal within-person changes. In a recent study, Bailey et al. demonstrated through a simulation study that the between-person variance components in the RICLPM can occur only due…
Descriptors: Longitudinal Studies, Correlation, Time, Simulation
Teague R. Henry; Zachary F. Fisher; Kenneth A. Bollen – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Model-Implied Instrumental Variable Two-Stage Least Squares (MIIV-2SLS) is a limited information, equation-by-equation, noniterative estimator for latent variable models. Associated with this estimator are equation-specific tests of model misspecification. One issue with equation-specific tests is that they lack specificity, in that they indicate…
Descriptors: Bayesian Statistics, Least Squares Statistics, Structural Equation Models, Equations (Mathematics)
Zsuzsa Bakk; Roberto Di Mari; Jennifer Oser; Jouni Kuha – Structural Equation Modeling: A Multidisciplinary Journal, 2022
In this article, we present a two-stage estimation approach applied to multilevel latent class analysis (LCA) with covariates. We separate the estimation of the measurement and structural model. This makes the extension of the structural model computationally efficient. We investigate the robustness against misspecifications of the proposed…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Computation, Measurement
Chunhua Cao; Benjamin Lugu; Jujia Li – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This study examined the false positive (FP) rates and sensitivity of Bayesian fit indices to structural misspecification in Bayesian structural equation modeling. The impact of measurement quality, sample size, model size, the magnitude of misspecified path effect, and the choice or prior on the performance of the fit indices was also…
Descriptors: Structural Equation Models, Bayesian Statistics, Measurement, Error of Measurement
Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…
Descriptors: Structural Equation Models, Bayesian Statistics, Comparative Analysis, Computation

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