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Austin, Peter C. – Multivariate Behavioral Research, 2012
Researchers are increasingly using observational or nonrandomized data to estimate causal treatment effects. Essential to the production of high-quality evidence is the ability to reduce or minimize the confounding that frequently occurs in observational studies. When using the potential outcome framework to define causal treatment effects, one…
Descriptors: Computation, Regression (Statistics), Statistical Bias, Error of Measurement
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Thoemmes, Felix J.; West, Stephen G. – Multivariate Behavioral Research, 2011
In this article we propose several modeling choices to extend propensity score analysis to clustered data. We describe different possible model specifications for estimation of the propensity score: single-level model, fixed effects model, and two random effects models. We also consider both conditioning within clusters and conditioning across…
Descriptors: Probability, Scores, Statistical Analysis, Models
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Cafri, Guy; Kromrey, Jeffrey D.; Brannick, Michael T. – Multivariate Behavioral Research, 2010
This article uses meta-analyses published in "Psychological Bulletin" from 1995 to 2005 to describe meta-analyses in psychology, including examination of statistical power, Type I errors resulting from multiple comparisons, and model choice. Retrospective power estimates indicated that univariate categorical and continuous moderators, individual…
Descriptors: Periodicals, Effect Size, Sampling, Psychology
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Rozeboom, William W. – Multivariate Behavioral Research, 2009
The topic of this article is the interpretation of structural equation modeling (SEM) solutions. Its purpose is to augment structural modeling's metatheoretic resources while enhancing awareness of how problematic is the causal significance of SEM-parameter solutions. Part I focuses on the nonuniqueness and consequent dubious interpretability of…
Descriptors: Structural Equation Models, Equations (Mathematics), Matrices, Probability
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Yuan, Ke-Hai – Multivariate Behavioral Research, 2008
In the literature of mean and covariance structure analysis, noncentral chi-square distribution is commonly used to describe the behavior of the likelihood ratio (LR) statistic under alternative hypothesis. Due to the inaccessibility of the rather technical literature for the distribution of the LR statistic, it is widely believed that the…
Descriptors: Monte Carlo Methods, Graduate Students, Social Sciences, Data Analysis
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Lee, Sik-Yum; Song, Xin-Yuan; Lu, Bin – Multivariate Behavioral Research, 2007
This article proposes an intuitive approach for predictive discriminant analysis with mixed continuous, dichotomous, and ordered categorical variables that are defined via an underlying multivariate normal distribution with a threshold specification. The classification rule is based on the comparison of the observed data logarithm probability…
Descriptors: Factor Analysis, Discriminant Analysis, Probability, Monte Carlo Methods
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Falk, Ruma; Well, Arnold D. – Multivariate Behavioral Research, 1996
One interpretation of the Pearson product-moment correlation ("r"), correlation as the probability of originating from common descent, important to the genetic measurement of inbreeding, is examined. The conditions under which "r" can be interpreted as the probability of "identity by descent" are specified, and the…
Descriptors: Correlation, Genetics, Heredity, Measurement Techniques
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Price, Lydia J. – Multivariate Behavioral Research, 1993
The ability of the NORMIX algorithm to recover overlapping population structures was compared to the OVERCLUS procedure and another clustering procedure in a Monte Carlo study. NORMIX is found to be more accurate than other procedures in recovering overlapping population structure when appropriate implementation options are specified. (SLD)
Descriptors: Algorithms, Classification, Cluster Analysis, Comparative Analysis