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Bishara, Anthony J.; Hittner, James B. – Educational and Psychological Measurement, 2015
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…
Descriptors: Research Methodology, Monte Carlo Methods, Correlation, Simulation

Glorfeld, Louis W. – Educational and Psychological Measurement, 1995
A modification of Horn's parallel analysis is introduced that is based on the Monte Carlo simulation of the null distributions of the eigenvalues generated from a population correlation identity matrix. This modification reduces the tendency of the parallel analysis procedure to overextract or to extract poorly defined factors. (SLD)
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices
Sawilowsky, Shlomo S.; Hillman, Stephen B. – 1991
Psychology studies often have low statistical power. Sample size tables, as given by J. Cohen (1988), may be used to increase power, but they are based on Monte Carlo studies of relatively "tame" mathematical distributions, as compared to psychology data sets. In this study, Monte Carlo methods were used to investigate Type I and Type II…
Descriptors: Mathematical Models, Monte Carlo Methods, Power (Statistics), Psychological Studies

Liew, Chong K.; And Others – Journal of the American Society for Information Science, 1985
Introduces two data distortion methods (Frequency-Imposed Distortion, Frequency-Imposed Probability Distortion) and uses a Monte Carlo study to compare their performance with that of other distortion methods (Point Distortion, Probability Distortion). Indications that data generated by these two methods produce accurate statistics and protect…
Descriptors: College Faculty, Comparative Analysis, Data Processing, Monte Carlo Methods

Schiel, Jeffrey L.; Shaw, Dale G. – Applied Measurement in Education, 1992
Changes in information retention resulting from changes in reliability and number of intervals in scale construction were studied to provide quantitative information to help in decisions about choosing intervals. Information retention reached a maximum when the number of intervals was about 8 or more and reliability was near 1.0. (SLD)
Descriptors: Decision Making, Knowledge Level, Mathematical Models, Monte Carlo Methods