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Huang, Po-Hsien; Weng, Li-Jen – Multivariate Behavioral Research, 2012
A procedure for estimating the reliability of test scores in the context of ecological momentary assessment (EMA) was proposed to take into account the characteristics of EMA measures. Two commonly used test scores in EMA were considered: the aggregated score (AGGS) and the within-person centered score (WPCS). Conceptually, AGGS and WPCS represent…
Descriptors: Reliability, Scores, Correlation, Computation
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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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Wang, Lijuan; Grimm, Kevin J. – Multivariate Behavioral Research, 2012
Reliabilities of the two most widely used intraindividual variability indicators, "ISD[superscript 2]" and "ISD", are derived analytically. Both are functions of the sizes of the first and second moments of true intraindividual variability, the size of the measurement error variance, and the number of assessments within a burst. For comparison,…
Descriptors: Reliability, Statistical Analysis, Measurement, Models
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Estabrook, Ryne; Neale, Michael – Multivariate Behavioral Research, 2013
Factor score estimation is a controversial topic in psychometrics, and the estimation of factor scores from exploratory factor models has historically received a great deal of attention. However, both confirmatory factor models and the existence of missing data have generally been ignored in this debate. This article presents a simulation study…
Descriptors: Factor Analysis, Scores, Computation, Regression (Statistics)
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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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Gottschall, Amanda C.; West, Stephen G.; Enders, Craig K. – Multivariate Behavioral Research, 2012
Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale…
Descriptors: Questionnaires, Data Analysis, Computation, Monte Carlo Methods
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Pituch, Keenan A.; Stapleton, Laura M. – Multivariate Behavioral Research, 2008
A Monte Carlo study compared the statistical performance of standard and robust multilevel mediation analysis methods to test indirect effects for a cluster randomized experimental design under various departures from normality. The performance of these methods was examined for an upper-level mediation process, where the indirect effect is a fixed…
Descriptors: Research Design, Monte Carlo Methods, Statistical Analysis, Error Patterns
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Krishnamoorthy, K.; Xia, Yanping – Multivariate Behavioral Research, 2008
The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…
Descriptors: Statistical Analysis, Intervals, Sample Size, Testing
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Sijtsma, Klaas; van der Ark, L. Andries – Multivariate Behavioral Research, 2003
This article first discusses a statistical test for investigating whether or not the pattern of missing scores in a respondent-by-item data matrix is random. Since this is an asymptotic test, we investigate whether it is useful in small but realistic sample sizes. Then, we discuss two known simple imputation methods, person mean (PM) and two-way…
Descriptors: Test Items, Questionnaires, Statistical Analysis, Models
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Zijlstra, Wobbe P.; Van Der Ark, L. Andries; Sijtsma, Klaas – Multivariate Behavioral Research, 2007
Classical methods for detecting outliers deal with continuous variables. These methods are not readily applicable to categorical data, such as incorrect/correct scores (0/1) and ordered rating scale scores (e.g., 0,..., 4) typical of multi-item tests and questionnaires. This study proposes two definitions of outlier scores suited for categorical…
Descriptors: Rating Scales, Scores, Regression (Statistics), Statistical Analysis