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Kelcey, Ben – Multivariate Behavioral Research, 2011
This study examined the practical problem of covariate selection in propensity scores (PSs) given a predetermined set of covariates. Because the bias reduction capacity of a confounding covariate is proportional to the concurrent relationships it has with the outcome and treatment, particular focus is set on how we might approximate…
Descriptors: Probability, Scores, Predictor Variables, Selection
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Thoemmes, Felix J.; Kim, Eun Sook – Multivariate Behavioral Research, 2011
The use of propensity scores in psychological and educational research has been steadily increasing in the last 2 to 3 years. However, there are some common misconceptions about the use of different estimation techniques and conditioning choices in the context of propensity score analysis. In addition, reporting practices for propensity score…
Descriptors: Social Science Research, Probability, Statistical Analysis, Computation
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Ruscio, John; Mullen, Tara – Multivariate Behavioral Research, 2012
It is good scientific practice to the report an appropriate estimate of effect size and a confidence interval (CI) to indicate the precision with which a population effect was estimated. For comparisons of 2 independent groups, a probability-based effect size estimator (A) that is equal to the area under a receiver operating characteristic curve…
Descriptors: Computation, Statistical Analysis, Probability, Effect Size
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Austin, Peter C. – Multivariate Behavioral Research, 2011
The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing…
Descriptors: Probability, Scores, Statistical Analysis, Computation
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Jo, Booil; Stuart, Elizabeth A.; MacKinnon, David P.; Vinokur, Amiram D. – Multivariate Behavioral Research, 2011
Mediation analysis uses measures of hypothesized mediating variables to test theory for how a treatment achieves effects on outcomes and to improve subsequent treatments by identifying the most efficient treatment components. Most current mediation analysis methods rely on untested distributional and functional form assumptions for valid…
Descriptors: Probability, Scores, Statistical Analysis, Computation
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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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Lottridge, Susan M.; Nicewander, W. Alan; Mitzel, Howard C. – Multivariate Behavioral Research, 2011
This inquiry had 2 components: (1) the first was substantive and focused on the comparability of paper-based and computer-based test forms and (2) the second was a within-study comparison wherein a quasi-experimental method, propensity score matching, was compared with a credible benchmark method, a within-subjects design. The tests used in the…
Descriptors: Comparative Analysis, Probability, Scores, Statistical Analysis
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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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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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Henschke, Claudia I.; And Others – Multivariate Behavioral Research, 1974
The technique presented accomodates multiple populations and a mixture of variable types. It is based on the linear discriminant function and the sequential concept. Also presented is an example in which the technique is used to obtain the classification rule to predict the career choices of individuals based upon a mixture of variable types.…
Descriptors: Classification, Measurement Techniques, Predictor Variables, Probability
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Huberty, Carl J.; Blommers, Paul J. – Multivariate Behavioral Research, 1974
Descriptors: Analysis of Covariance, Analysis of Variance, Classification, Discriminant Analysis