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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
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

Tisak, John – Multivariate Behavioral Research, 1994
The regression coefficients and the associated standard errors in hierarchical regression, when a theoretical basis for the analysis exists, are determined for four regression models. Each reflects different controlling or partialling of the variates. An illustration is presented using data from the Berkeley Growth Study. (SLD)
Descriptors: Comparative Analysis, Error of Measurement, Estimation (Mathematics), Predictor Variables

Feild, Hubert S.; And Others – Multivariate Behavioral Research, 1975
Empirically determines if two approaches, i.e., individual predictor information versus group information, would yield different predictive results, and since the second approach involved the additional expense of grouping whether the prediction of criterion measures by individual data could be enhanced by the addition of group data. (Author/RC)
Descriptors: College Students, Comparative Analysis, Correlation, Homogeneous Grouping

Anderson, Lance E.; And Others – Multivariate Behavioral Research, 1996
Simulations were used to compare the moderator variable detection capabilities of moderated multiple regression (MMR) and errors-in-variables regression (EIVR). Findings show that EIVR estimates are superior for large samples, but that MMR is better when reliabilities or sample sizes are low. (SLD)
Descriptors: Comparative Analysis, Error of Measurement, Estimation (Mathematics), Interaction