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McLachlan, Geoffrey J. – Psychological Methods, 2011
I discuss the recommendations and cautions in Steinley and Brusco's (2011) article on the use of finite models to cluster a data set. In their article, much use is made of comparison with the "K"-means procedure. As noted by researchers for over 30 years, the "K"-means procedure can be viewed as a special case of finite mixture modeling in which…
Descriptors: Computation, Multivariate Analysis, Matrices, Statistical Analysis
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Schimmack, Ulrich – Psychological Methods, 2012
Cohen (1962) pointed out the importance of statistical power for psychology as a science, but statistical power of studies has not increased, while the number of studies in a single article has increased. It has been overlooked that multiple studies with modest power have a high probability of producing nonsignificant results because power…
Descriptors: Psychological Studies, Statistical Analysis, Probability, Statistical Significance
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Manolov, Rumen; Solanas, Antonio – Psychological Methods, 2012
There is currently a considerable diversity of quantitative measures available for summarizing the results in single-case studies. Given that the interpretation of some of them is difficult due to the lack of established benchmarks, the current article proposes an approach for obtaining further numerical evidence on the importance of the results,…
Descriptors: Sampling, Probability, Statistical Significance, Case Studies
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Harder, Valerie S.; Stuart, Elizabeth A.; Anthony, James C. – Psychological Methods, 2010
There is considerable interest in using propensity score (PS) statistical techniques to address questions of causal inference in psychological research. Many PS techniques exist, yet few guidelines are available to aid applied researchers in their understanding, use, and evaluation. In this study, the authors give an overview of available…
Descriptors: Psychological Studies, Probability, Statistical Analysis, Statistical Inference
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Steiner, Peter M.; Cook, Thomas D.; Shadish, William R.; Clark, M. H. – Psychological Methods, 2010
The assumption of strongly ignorable treatment assignment is required for eliminating selection bias in observational studies. To meet this assumption, researchers often rely on a strategy of selecting covariates that they think will control for selection bias. Theory indicates that the most important covariates are those highly correlated with…
Descriptors: Selection, Bias, Observation, Comparative Analysis
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Keselman, H. J.; Algina, James; Lix, Lisa M.; Wilcox, Rand R.; Deering, Kathleen N. – Psychological Methods, 2008
Standard least squares analysis of variance methods suffer from poor power under arbitrarily small departures from normality and fail to control the probability of a Type I error when standard assumptions are violated. This article describes a framework for robust estimation and testing that uses trimmed means with an approximate degrees of…
Descriptors: Intervals, Testing, Least Squares Statistics, Effect Size