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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
Mayer, Axel; Steyer, Rolf; Mueller, Horst – Structural Equation Modeling: A Multidisciplinary Journal, 2012
We present a 3-step approach to defining latent growth components. In the first step, a measurement model with at least 2 indicators for each time point is formulated to identify measurement error variances and obtain latent variables that are purged from measurement error. In the second step, we use contrast matrices to define the latent growth…
Descriptors: Statistical Analysis, Measurement, Structural Equation Models, Error of Measurement
Depaoli, Sarah – Structural Equation Modeling: A Multidisciplinary Journal, 2012
Parameter recovery was assessed within mixture confirmatory factor analysis across multiple estimator conditions under different simulated levels of mixture class separation. Mixture class separation was defined in the measurement model (through factor loadings) and the structural model (through factor variances). Maximum likelihood (ML) via the…
Descriptors: Markov Processes, Factor Analysis, Statistical Bias, Evaluation Research
Landsheer, J. A. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Tetrad IV is a program designed for the specification of causal models. It is specifically designed to search for causal relations, but also offers the possibility to estimate the parameters of a structural equation model. It offers a remarkable graphical user interface, which facilitates building, evaluating, and searching for causal models. The…
Descriptors: Structural Equation Models, Causal Models, Evaluation, Mathematics
Hertzog, Christopher; von Oertzen, Timo; Ghisletta, Paolo; Lindenberger, Ulman – Structural Equation Modeling: A Multidisciplinary Journal, 2008
We evaluated the statistical power of single-indicator latent growth curve models to detect individual differences in change (variances of latent slopes) as a function of sample size, number of longitudinal measurement occasions, and growth curve reliability. We recommend the 2 degree-of-freedom generalized test assessing loss of fit when both…
Descriptors: Sample Size, Error of Measurement, Individual Differences, Statistical Analysis
Vlachopoulos, Symeon P. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
This study examined the extent of measurement invariance of the Basic Psychological Needs in Exercise Scale responses (BPNES; Vlachopoulos & Michailidou, 2006) across male (n = 716) and female (n = 1,147) exercise participants. BPNES responses from exercise participants attending private fitness centers (n = 1,012) and community exercise programs…
Descriptors: Psychological Patterns, Factor Structure, Measures (Individuals), Measurement