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Download full textMuthen, Bengt – 1994
This paper investigates methods that avoid using multiple groups to represent the missing data patterns in covariance structure modeling, attempting instead to do a single-group analysis where the only action the analyst has to take is to indicate that data is missing. A new covariance structure approach developed by B. Muthen and G. Arminger is…
Descriptors: Bayesian Statistics, Estimation (Mathematics), Maximum Likelihood Statistics, Monte Carlo Methods
Peer reviewedHarwell, Michael R. – Educational and Psychological Measurement, 1997
Results from two Monte Carlo studies in item response theory (comparisons of computer item analysis programs and Bayes estimation procedures) are analyzed with inferential methods to illustrate the procedures' strengths. It is recommended that researchers in item response theory use both descriptive and inferential methods to analyze Monte Carlo…
Descriptors: Bayesian Statistics, Comparative Analysis, Computer Software, Estimation (Mathematics)
Peer reviewedCohen, Jon; Snow, Stephanie – Journal of Educational Measurement, 2002
Studied the impact of changes in item difficulty on National Assessment of Educational Progress (NAEP) estimates over time through a Monte Carlo study that simulated the responses of 1990 NAEP mathematics respondents to 1990 and 1996 NAEP mathematics items. Results support the idea that these changes have not affected the NAEP trend line.…
Descriptors: Change, Difficulty Level, Estimation (Mathematics), Mathematics Tests
