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Stone, Clement A.; Yeh, Chien-Chi – Educational and Psychological Measurement, 2006
Examination of a test's internal structure can be used to identify what domains or dimensions are being measured, identify relationships between the dimensions, provide evidence for hypothesized multidimensionality and test score interpretations, and identify construct-irrelevant variance. The purpose of this research is to provide a…
Descriptors: Multiple Choice Tests, Factor Structure, Factor Analysis, Licensing Examinations (Professions)
Peer reviewed
Cota, Albert A.; And Others – Educational and Psychological Measurement, 1993
Focusing on linear interpolation, an accurate method of implementing parallel analysis, this article contains tables of 95th percentile eigenvalues from random data than can be used with sample sizes of 50 to 500 subjects and between 5 and 50 variables. An empirical example illustrates how to obtain the eigenvalues. (SLD)
Descriptors: Comparative Analysis, Computation, Factor Analysis, Monte Carlo Methods
Peer reviewed
Smith, Richard M.; Kramer, Gene A. – Educational and Psychological Measurement, 1992
The common item equating method (weighted and unweighted) and the one-step missing data calibration method used with Rasch measurement models were compared using data from six equivalent forms of a perceptual ability test administered as part of the Dental Admission Test. Results suggest little difference among the equating methods. (SLD)
Descriptors: Ability, Aptitude Tests, College Entrance Examinations, Comparative Analysis
Peer reviewed
Parshall, Cynthia G.; Kromrey, Jeffrey D. – Educational and Psychological Measurement, 1996
Power and Type I error rates were estimated for contingency tables with small sample sizes for the following four types of tests: (1) Pearson's chi-square; (2) chi-square with Yates's continuity correction; (3) the likelihood ratio test; and (4) Fisher's Exact Test. Various marginal distributions, sample sizes, and effect sizes were examined. (SLD)
Descriptors: Chi Square, Comparative Analysis, Effect Size, Estimation (Mathematics)
Peer reviewed
Smith, Richard M. – Educational and Psychological Measurement, 1996
The separate calibration t-test approach of B. Wright and M. Stone (1979) and the common calibration between-fit approach of B. Wright, R. Mead, and R. Draba (1976) appeared to have similar Type I error rates and similar power to detect item bias within a Rasch framework. (SLD)
Descriptors: Comparative Analysis, Goodness of Fit, Item Bias, Item Response Theory