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Direct linkVoelkle, Manuel C.; Oud, Johan H. L.; Davidov, Eldad; Schmidt, Peter – Psychological Methods, 2012
Panel studies, in which the same subjects are repeatedly observed at multiple time points, are among the most popular longitudinal designs in psychology. Meanwhile, there exists a wide range of different methods to analyze such data, with autoregressive and cross-lagged models being 2 of the most well known representatives. Unfortunately, in these…
Descriptors: Authoritarianism, Intervals, Structural Equation Models, Correlation
McGrath, Robert E.; Walters, Glenn D. – Psychological Methods, 2012
Statistical analyses investigating latent structure can be divided into those that estimate structural model parameters and those that detect the structural model type. The most basic distinction among structure types is between categorical (discrete) and dimensional (continuous) models. It is a common, and potentially misleading, practice to…
Descriptors: Factor Structure, Factor Analysis, Monte Carlo Methods, Computation
Muthen, Bengt; Asparouhov, Tihomir – Psychological Methods, 2012
This article proposes a new approach to factor analysis and structural equation modeling using Bayesian analysis. The new approach replaces parameter specifications of exact zeros with approximate zeros based on informative, small-variance priors. It is argued that this produces an analysis that better reflects substantive theories. The proposed…
Descriptors: Factor Analysis, Cognitive Ability, Science Achievement, Structural Equation Models
Eid, Michael; Nussbeck, Fridtjof W.; Geiser, Christian; Cole, David A.; Gollwitzer, Mario; Lischetzke, Tanja – Psychological Methods, 2008
The question as to which structural equation model should be selected when multitrait-multimethod (MTMM) data are analyzed is of interest to many researchers. In the past, attempts to find a well-fitting model have often been data-driven and highly arbitrary. In the present article, the authors argue that the measurement design (type of methods…
Descriptors: Structural Equation Models, Multitrait Multimethod Techniques, Statistical Analysis, Error of Measurement
Cheung, Mike W. L.; Chan, Wai – Psychological Methods, 2005
To synthesize studies that use structural equation modeling (SEM), researchers usually use Pearson correlations (univariate r), Fisher z scores (univariate z), or generalized least squares (GLS) to combine the correlation matrices. The pooled correlation matrix is then analyzed by the use of SEM. Questionable inferences may occur for these ad hoc…
Descriptors: Inferences, Meta Analysis, Least Squares Statistics, Structural Equation Models
Furlow, Carolyn F.; Beretvas, S. Natasha – Psychological Methods, 2005
Three methods of synthesizing correlations for meta-analytic structural equation modeling (SEM) under different degrees and mechanisms of missingness were compared for the estimation of correlation and SEM parameters and goodness-of-fit indices by using Monte Carlo simulation techniques. A revised generalized least squares (GLS) method for…
Descriptors: Rejection (Psychology), Monte Carlo Methods, Least Squares Statistics, Correlation
