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Enders, Craig K. – Guilford Press, 2010
Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and…
Descriptors: Data Analysis, Error of Measurement, Research Problems, Maximum Likelihood Statistics
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Finch, Holmes; Monahan, Patrick – Applied Measurement in Education, 2008
This article introduces a bootstrap generalization to the Modified Parallel Analysis (MPA) method of test dimensionality assessment using factor analysis. This methodology, based on the use of Marginal Maximum Likelihood nonlinear factor analysis, provides for the calculation of a test statistic based on a parametric bootstrap using the MPA…
Descriptors: Monte Carlo Methods, Factor Analysis, Generalization, Methods