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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Some General Guidelines For Choosing Missing Data Handling Methods In Educational Research, Jehanzeb R. Cheema
Some General Guidelines For Choosing Missing Data Handling Methods In Educational Research, Jehanzeb R. Cheema
Journal of Modern Applied Statistical Methods
The effect of a number of factors, such as the choice of analytical method, the handling method for missing data, sample size, and proportion of missing data, were examined to evaluate the effect of missing data treatment on accuracy of estimation. A methodological approach involving simulated data was adopted. One outcome of the statistical analyses undertaken in this study is the formulation of easy-to-implement guidelines for educational researchers that allows one to choose one of the following factors when all others are given: sample size, proportion of missing data in the sample, method of analysis, and missing data handling method.
The Treatment Of Missing Data When Estimating Student Growth With Pre-Post Educational Accountability Data, Jason P. Kopp
The Treatment Of Missing Data When Estimating Student Growth With Pre-Post Educational Accountability Data, Jason P. Kopp
Dissertations, 2014-2019
To ensure program quality and meet accountability mandates, it is becoming increasingly important for educational institutions to show “value-added” for attending students. Value-added is often evidenced by some form of pre-post assessment, where a change in scores on a construct of interest is considered indicative of student growth. Although missing data is a common problem for these pre-post designs, missingness is rarely addressed and cases with missing data are often listwise deleted. The current study examined the mechanism underlying, and bias resulting from, missingness due to posttest nonattendance in a higher-education accountability testing context. Although data were missing for some …