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Vallejo, G.; Fernandez, M. P.; Livacic-Rojas, P. E.; Tuero-Herrero, E. – Multivariate Behavioral Research, 2011
Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…
Descriptors: Personality Problems, Psychosis, Prevention, Patients
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Maraun, Michael D.; Slaney, Kathleen – Multivariate Behavioral Research, 2005
MAXCOV-HITMAX was invented by Paul Meehl as a tool for the detection of latent taxonic structures (i.e., structures in which the latent variable, u, is not continuously, but rather Bernoulli, distributed). It involves the examination of the shape of a certain conditional covariance function and is based on Meehl's claims that (R1) Taxonic…
Descriptors: Multivariate Analysis, Hypothesis Testing, Monte Carlo Methods, Behavioral Science Research
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Blair, R. Clifford; And Others – Multivariate Behavioral Research, 1994
Multivariate permutation tests are described, and some are suggested as substitutions for Hotelling's one-sample T2 test in common situations in behavioral science research. A Monte Carlo study shows advantages of these tests when the T2 test fails or is suspect. (SLD)
Descriptors: Behavioral Science Research, Correlation, Graphs, Hypothesis Testing
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Lambert, Zarrel V.; And Others – Multivariate Behavioral Research, 1991
A method is presented that eliminates some interpretational limitations arising from assumptions implicit in the use of arbitrary rules of thumb to interpret exploratory factor analytic results. The bootstrap method is presented as a way of approximating sampling distributions of estimated factor loadings. Simulated datasets illustrate the…
Descriptors: Behavioral Science Research, Computer Simulation, Estimation (Mathematics), Factor Structure
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Huberty, Carl J.; DiStefano, Christine; Kamphaus, Randy W. – Multivariate Behavioral Research, 1997
How a cluster analysis is conducted, validated, and interpreted is illustrated using a 14-scale behavioral assessment instrument and a national sample of 1,228 elementary school students. Method, cluster typology, validity, cluster structure, and prediction of cluster membership are discussed. (Author/SLD)
Descriptors: Behavior Rating Scales, Behavioral Science Research, Cluster Analysis, Elementary Education
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Shieh, Gwowen – Multivariate Behavioral Research, 2003
Repeated measures and longitudinal studies arise often in social and behavioral science research. During the planning stage of such studies, the calculations of sample size are of particular interest to the investigators and should be an integral part of the research projects. In this article, we consider the power and sample size calculations for…
Descriptors: Comparative Analysis, Behavioral Science Research, Monte Carlo Methods, Longitudinal Studies
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Mills, Jamie, D.; Olejnik, Stephen, F.; Marcoulides, George, A. – Multivariate Behavioral Research, 2005
The effectiveness of the Tabu variable selection algorithm, to identify predictor variables related to a criterion variable, is compared with the stepwise variable selection method and the all possible regression approach. Considering results obtained from previous research, Tabu is more successful in identifying relevant variables than the…
Descriptors: Predictor Variables, Multiple Regression Analysis, Behavioral Science Research, Evaluation Criteria
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Wiggins, Jerry S. – Multivariate Behavioral Research, 1984
This overview of the field of personality theory evaluates the important features of Raymond Cattell's work. While there are many areas of agreement between Cattell and other personality theorists, his rejection of traditional clinical methods for measurement and experimentation has created controversy as well as an extraordinarily rich…
Descriptors: Behavior Theories, Behavioral Science Research, Clinical Psychology, Experimental Psychology