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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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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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Austin, Peter C. – Multivariate Behavioral Research, 2011
Propensity score methods allow investigators to estimate causal treatment effects using observational or nonrandomized data. In this article we provide a practical illustration of the appropriate steps in conducting propensity score analyses. For illustrative purposes, we use a sample of current smokers who were discharged alive after being…
Descriptors: Smoking, Hospitals, Program Effectiveness, Probability
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Maydeu-Olivares, Alberto; Brown, Anna – Multivariate Behavioral Research, 2010
The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally…
Descriptors: Item Response Theory, Rating Scales, Models, Comparative Analysis
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Steinley, Douglas; Brusco, Michael J. – Multivariate Behavioral Research, 2008
A variance-to-range ratio variable weighting procedure is proposed. We show how this weighting method is theoretically grounded in the inherent variability found in data exhibiting cluster structure. In addition, a variable selection procedure is proposed to operate in conjunction with the variable weighting technique. The performances of these…
Descriptors: Test Items, Simulation, Multivariate Analysis, Data Analysis
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van Ginkel, Joost R.; van der Ark, L. Andries; Sijtsma, Klaas – Multivariate Behavioral Research, 2007
The performance of five simple multiple imputation methods for dealing with missing data were compared. In addition, random imputation and multivariate normal imputation were used as lower and upper benchmark, respectively. Test data were simulated and item scores were deleted such that they were either missing completely at random, missing at…
Descriptors: Evaluation Methods, Psychometrics, Item Response Theory, Scores
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Labouvie, Erich; And Others – Multivariate Behavioral Research, 1995
Twelve articles (including two rounds of commentary) consider the proposition that the use of multi-item scales requires only that conditions of simple structure and metric invariance be satisfied at the scale level, rather than for each item individually. The place of the approach in confirmatory factor analysis is debated. (SLD)
Descriptors: Comparative Analysis, Equations (Mathematics), Factor Structure, Measures (Individuals)
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Grice, James W.; Harris, Richard J. – Multivariate Behavioral Research, 1998
An alternative strategy for computing factor scores was introduced and compared to a popular scoring procedure. The new strategy, which involves unit-weighted composites of standardized items with salient factor score coefficients, is shown superior to the common method. Implications of findings are discussed. (SLD)
Descriptors: Comparative Analysis, Factor Analysis, Factor Structure, Regression (Statistics)
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Suziedelis, Antanas; And Others – Multivariate Behavioral Research, 1976
A method of typological analysis was applied to computer-generated 96-item questionnaire data for 100 cases, under a variety of conditions to analyze both the item-level and score-level. The results showed a considerable advantage of score-level approach in the number, size, and replicability of clusters recovered. (DEP)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Comparative Analysis
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Fava, Joseph L.; Velicer, Wayne F. – Multivariate Behavioral Research, 1992
Principal component, image component, three types of factor score estimates, and one scale score method were compared over different levels of variables, saturations, sample sizes, variable to component ratios, and pattern rotations. There were virtually no overall differences among methods, with the average correlation between matched scores…
Descriptors: Comparative Analysis, Correlation, Equations (Mathematics), Estimation (Mathematics)