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Handling Missing Data in Educational Research Using SPSS

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dc.contributor.advisor Dimitrov, Dimiter M. Cheema, Jehanzeb
dc.creator Cheema, Jehanzeb 2012-04-03 2012-05-31T18:04:31Z NO_RESTRICTION en_US 2012-05-31T18:04:31Z 2012-05-31
dc.description.abstract This study looked at 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, in order to evaluate the effect of missing data treatment on accuracy of estimation. In order to accomplish this 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.
dc.language.iso en
dc.subject Imputation Method en_US
dc.subject Item Non-Response en_US
dc.subject Listwise Deletion en_US
dc.subject Missing Data en_US
dc.subject Multiple Imputation en_US
dc.subject Missing Value en_US
dc.title Handling Missing Data in Educational Research Using SPSS
dc.type Dissertation PhD in Education en_US Doctoral Education George Mason University

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