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Lee, Daniel Y.; Harring, Jeffrey R. – Journal of Educational and Behavioral Statistics, 2023
A Monte Carlo simulation was performed to compare methods for handling missing data in growth mixture models. The methods considered in the current study were (a) a fully Bayesian approach using a Gibbs sampler, (b) full information maximum likelihood using the expectation-maximization algorithm, (c) multiple imputation, (d) a two-stage multiple…
Descriptors: Monte Carlo Methods, Research Problems, Statistical Inference, Bayesian Statistics
Nandakumar, Ratna – 1988
The effectiveness of Stout's procedure for assessing latent trait unidimensionality was studied. Strong empirical evidence of the utility of the statistical test in a variety of settings is provided. The procedure was modified to correct for increased bias, and a new algorithm to determine the size of assessment sub-tests was used. The following…
Descriptors: Algorithms, Latent Trait Theory, Monte Carlo Methods, Standardized Tests