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Choosing the Optimal Number of Factors in Exploratory Factor Analysis: A Model Selection Perspective
Peer reviewed
Direct linkPreacher, Kristopher J.; Zhang, Guangjian; Kim, Cheongtag; Mels, Gerhard – Multivariate Behavioral Research, 2013
A central problem in the application of exploratory factor analysis is deciding how many factors to retain ("m"). Although this is inherently a model selection problem, a model selection perspective is rarely adopted for this task. We suggest that Cudeck and Henly's (1991) framework can be applied to guide the selection process.…
Descriptors: Factor Analysis, Models, Selection, Goodness of Fit
Tong, Xin; Zhang, Zhiyong – Multivariate Behavioral Research, 2012
Growth curve models with different types of distributions of random effects and of intraindividual measurement errors for robust analysis are compared. After demonstrating the influence of distribution specification on parameter estimation, 3 methods for diagnosing the distributions for both random effects and intraindividual measurement errors…
Descriptors: Models, Robustness (Statistics), Statistical Analysis, Error of Measurement
Sterba, Sonya K. – Multivariate Behavioral Research, 2009
A model-based framework, due originally to R. A. Fisher, and a design-based framework, due originally to J. Neyman, offer alternative mechanisms for inference from samples to populations. We show how these frameworks can utilize different types of samples (nonrandom or random vs. only random) and allow different kinds of inference (descriptive vs.…
Descriptors: Statistical Inference, Models, Sampling, Psychology
Marsh, Herbert W.; Ludtke, Oliver; Robitzsch, Alexander; Trautwein, Ulrich; Asparouhov, Tihomir; Muthen, Bengt; Nagengast, Benjamin – Multivariate Behavioral Research, 2009
This article is a methodological-substantive synergy. Methodologically, we demonstrate latent-variable contextual models that integrate structural equation models (with multiple indicators) and multilevel models. These models simultaneously control for and unconfound measurement error due to sampling of items at the individual (L1) and group (L2)…
Descriptors: Educational Environment, Context Effect, Models, Structural Equation Models
