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Steinley, Douglas; Brusco, Michael J. – Psychological Methods, 2011
McLachlan (2011) and Vermunt (2011) each provided thoughtful replies to our original article (Steinley & Brusco, 2011). This response serves to incorporate some of their comments while simultaneously clarifying our position. We argue that greater caution against overparamaterization must be taken when assuming that clusters are highly elliptical…
Descriptors: Multivariate Analysis, Research Methodology, Data, Models
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Vermunt, Jeroen K. – Psychological Methods, 2011
Steinley and Brusco (2011) presented the results of a huge simulation study aimed at evaluating cluster recovery of mixture model clustering (MMC) both for the situation where the number of clusters is known and is unknown. They derived rather strong conclusions on the basis of this study, especially with regard to the good performance of…
Descriptors: Multivariate Analysis, Simulation, Research, Mathematics
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Enders, Craig K. – Psychological Methods, 2011
The past decade has seen a noticeable shift in missing data handling techniques that assume a missing at random (MAR) mechanism, where the propensity for missing data on an outcome is related to other analysis variables. Although MAR is often reasonable, there are situations where this assumption is unlikely to hold, leading to biased parameter…
Descriptors: Structural Equation Models, Social Sciences, Data, Attrition (Research Studies)
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Savalei, Victoria – Psychological Methods, 2010
Maximum likelihood is the most common estimation method in structural equation modeling. Standard errors for maximum likelihood estimates are obtained from the associated information matrix, which can be estimated from the sample using either expected or observed information. It is known that, with complete data, estimates based on observed or…
Descriptors: Structural Equation Models, Computation, Error of Measurement, Data
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Slaney, Kathleen L.; Maraun, Michael D. – Psychological Methods, 2008
The authors argue that the current state of applied data-based test analytic practice is unstructured and unmethodical due in large part to the fact that there is no clearly specified, widely accepted test analytic framework for judging the performances of particular tests in particular contexts. Drawing from the extant test theory literature,…
Descriptors: Test Theory, Data, Test Validity, Models
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Brusco, Michael J.; Steinley, Douglas – Psychological Methods, 2006
The study of confusion data is a well established practice in psychology. Although many types of analytical approaches for confusion data are available, among the most common methods are the extraction of 1 or more subsets of stimuli, the partitioning of the complete stimulus set into distinct groups, and the ordering of the stimulus set. Although…
Descriptors: Stimuli, Multivariate Analysis, Psychology, Data
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Takarangi, Melanie K. T.; Garry, Maryanne; Loftus, Elizabeth F. – Psychological Methods, 2006
In this commentary, the authors discuss the implications of A. S. Green, E. Rafaeli, N. Bolger, P. E. Shrout, and H. T. Reis's (2006) diary studies with respect to memory. Researchers must take 2 issues into account when determining whether paper-and-pencil or handheld electronic diaries gather more trustworthy data. The first issue is a matter of…
Descriptors: Computer Mediated Communication, Paper (Material), Compliance (Psychology), Validity