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Rasmussen, Jeffrey Lee; Dunlap, William P. – Educational and Psychological Measurement, 1991
Results of a Monte Carlo study with 4 populations (3,072 conditions) indicate that when distributions depart markedly from normality, nonparametric analysis and parametric analysis of transformed data show superior power to parametric analysis of raw data. Under conditions studied, parametric analysis of transformed data is more powerful than…
Descriptors: Comparative Analysis, Computer Simulation, Monte Carlo Methods, Power (Statistics)

Smith, Richard M. – Educational and Psychological Measurement, 1988
This study investigated the distributional properties of the standardized residual that is commonly used in the Rasch model calibration program to develop various indices of item and person fit. The power of the standardized residual to detect measurement disturbances is also addressed. (TJH)
Descriptors: Computer Simulation, Error of Measurement, Goodness of Fit, Guessing (Tests)

Smith, Richard M. – Educational and Psychological Measurement, 1991
This study reports results of an investigation based on simulated data of the distributional properties of the item fit statistics that are commonly used in the Rasch model calibration programs as indices of the fit of responses to individual items to the measurement model. (SLD)
Descriptors: Computer Simulation, Equations (Mathematics), Goodness of Fit, Item Response Theory

Brown, R. L. – Educational and Psychological Measurement, 1992
A Monte Carlo study explores the robustness assumption in structural equation modeling of using a full information normal theory generalized least-squares estimation procedure on Type I censored data. The efficacy of the following proposed alternate estimation procedures is assessed: asymptotically distribution free estimator and a latent…
Descriptors: Computer Simulation, Equations (Mathematics), Estimation (Mathematics), Least Squares Statistics

Dodd, Barbara G.; And Others – Educational and Psychological Measurement, 1993
Effects of the following variables on performance of computerized adaptive testing (CAT) procedures for the partial credit model (PCM) were studied: (1) stopping rule for terminating CAT; (2) item pool size; and (3) distribution of item difficulties. Implications of findings for CAT systems based on the PCM are discussed. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Simulation, Difficulty Level