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Download full textPuma, Michael J.; Olsen, Robert B.; Bell, Stephen H.; Price, Cristofer – National Center for Education Evaluation and Regional Assistance, 2009
This NCEE Technical Methods report examines how to address the problem of missing data in the analysis of data in Randomized Controlled Trials (RCTs) of educational interventions, with a particular focus on the common educational situation in which groups of students such as entire classrooms or schools are randomized. Missing outcome data are a…
Descriptors: Educational Research, Research Design, Research Methodology, Control Groups
Direct linkFinch, 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
Peer reviewedCroy, Calvin D.; Novins, Douglas K. – Journal of the American Academy of Child and Adolescent Psychiatry, 2005
Objective: First, to provide information about best practices in handling missing data so that readers can judge the quality of research studies. Second, to provide more detailed information about missing data analysis techniques and software on the Journal's Web site at www.jaacap.com. Method: We focus our review of techniques on those that are…
Descriptors: Information Needs, Data Collection, Statistical Analysis, Maximum Likelihood Statistics
