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Keller, Bryan S. B.; Kim, Jee-Seon; Steiner, Peter M. – Society for Research on Educational Effectiveness, 2013
Propensity score analysis (PSA) is a methodological technique which may correct for selection bias in a quasi-experiment by modeling the selection process using observed covariates. Because logistic regression is well understood by researchers in a variety of fields and easy to implement in a number of popular software packages, it has…
Descriptors: Probability, Scores, Statistical Analysis, Statistical Bias
Ackerman, Terry A. – 1991
This paper examines the effect of using unidimensional item response theory (IRT) item parameter estimates of multidimensional items to create weakly parallel test forms using target information curves. To date, all computer-based algorithms that have been devised to create parallel test forms assume that the items are unidimensional. This paper…
Descriptors: Algorithms, Equations (Mathematics), Estimation (Mathematics), Item Response Theory
Schumacker, Randall E.; Fluke, Rickey – 1991
Three methods of factor analyzing dichotomously scored item performance data were compared using two raw score data sets of 20-item tests, one reflecting normally distributed latent traits and the other reflecting uniformly distributed latent traits. This comparison was accomplished by using phi and tetrachoric correlations among dichotomous data…
Descriptors: Comparative Analysis, Equations (Mathematics), Estimation (Mathematics), Factor Analysis
Spray, Judith A.; Welch, Catherine J. – 1986
The purpose of this study was to examine the effect that large within-examinee item difficulty variability had on estimates of the proportion of consistent classification of examinees into mastery categories over two test administrations. The classification consistency estimate was based on a single test administration from an estimation procedure…
Descriptors: Adults, Difficulty Level, Estimation (Mathematics), Mathematical Models
Reckase, Mark D. – 1978
Five comparisons were made relative to the quality of estimates of ability parameters and item calibrations obtained from the one-parameter and three-parameter logistic models. The results indicate: (1) The three-parameter model fit the test data better in all cases than did the one-parameter model. For simulation data sets, multi-factor data were…
Descriptors: Comparative Analysis, Goodness of Fit, Item Analysis, Mathematical Models