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Zopluoglu, Cengiz – Educational and Psychological Measurement, 2020
A mixture extension of Samejima's continuous response model for continuous measurement outcomes and its estimation through a heuristic approach based on limited-information factor analysis is introduced. Using an empirical data set, it is shown that two groups of respondents that differ both qualitatively and quantitatively in their response…
Descriptors: Item Response Theory, Measurement, Models, Heuristics
Montoya, Amanda K.; Edwards, Michael C. – Educational and Psychological Measurement, 2021
Model fit indices are being increasingly recommended and used to select the number of factors in an exploratory factor analysis. Growing evidence suggests that the recommended cutoff values for common model fit indices are not appropriate for use in an exploratory factor analysis context. A particularly prominent problem in scale evaluation is the…
Descriptors: Goodness of Fit, Factor Analysis, Cutting Scores, Correlation
Huang, Francis L. – Educational and Psychological Measurement, 2018
Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials…
Descriptors: Multivariate Analysis, Sampling, Statistical Inference, Data Analysis
Dardick, William R.; Mislevy, Robert J. – Educational and Psychological Measurement, 2016
A new variant of the iterative "data = fit + residual" data-analytical approach described by Mosteller and Tukey is proposed and implemented in the context of item response theory psychometric models. Posterior probabilities from a Bayesian mixture model of a Rasch item response theory model and an unscalable latent class are expressed…
Descriptors: Bayesian Statistics, Probability, Data Analysis, Item Response Theory
Green, Samuel B.; Levy, Roy; Thompson, Marilyn S.; Lu, Min; Lo, Wen-Juo – Educational and Psychological Measurement, 2012
A number of psychometricians have argued for the use of parallel analysis to determine the number of factors. However, parallel analysis must be viewed at best as a heuristic approach rather than a mathematically rigorous one. The authors suggest a revision to parallel analysis that could improve its accuracy. A Monte Carlo study is conducted to…
Descriptors: Monte Carlo Methods, Factor Structure, Data Analysis, Psychometrics
Cho, Sun-Joo; Li, Feiming; Bandalos, Deborah – Educational and Psychological Measurement, 2009
The purpose of this study was to investigate the application of the parallel analysis (PA) method for choosing the number of factors in component analysis for situations in which data are dichotomous or ordinal. Although polychoric correlations are sometimes used as input for component analyses, the random data matrices generated for use in PA…
Descriptors: Correlation, Evaluation Methods, Data Analysis, Matrices
Zimmerman, Donald W. – Educational and Psychological Measurement, 2007
Properties of the Spearman correction for attenuation were investigated using Monte Carlo methods, under conditions where correlations between error scores exist as a population parameter and also where correlated errors arise by chance in random sampling. Equations allowing for all possible dependence among true and error scores on two tests at…
Descriptors: Monte Carlo Methods, Correlation, Sampling, Data Analysis

Renner, Barbara Rochen; Ball, Donald W. – Educational and Psychological Measurement, 1983
To determine the effect of violating the assumption of homogeneity of covariance for the Tukey Wholly Significant Difference (WSD) test, Monte Carlo simulations varied the number of treatment groups, sample size, and degree of covariance heterogeneity. As covariance heterogeneity was increased, the empirical significance levels increased beyond…
Descriptors: Data Analysis, Hypothesis Testing, Monte Carlo Methods, Research Methodology

Lathrop, Richard G.; Williams, Janice E. – Educational and Psychological Measurement, 1990
A Monte Carlo study of the validity of the Inverse Scree Test under conditions where true group membership is known was conducted. Fifty cluster analyses of each distribution involving 2 to 5 true groups of 3,000 simulated subjects were made. Implications for the data analyst are discussed. (SLD)
Descriptors: Cluster Analysis, Data Analysis, Group Membership, Monte Carlo Methods

Carroll, Robert M. – Educational and Psychological Measurement, 1976
Examines the similarity between the coordinates which resulted when correlations were used as similarity measures and the factor loadings obtained by factor analyzing the same correlation matrix. Real data, a set of error free data, and some computer generated data containing deliberately introduced sampling error are analyzed. (RC)
Descriptors: Comparative Analysis, Correlation, Data Analysis, Factor Analysis