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Exploring Listwise Deletion And Multilevel Multiple Imputation In Linear Two-Level Organizational Models, Whitney Flemming Smiley

Theses and Dissertations

Problems of missing data are pervasive in social science research. Because of this, researchers have begun to use techniques after data collection to deal with missing data, including traditional methods (i.e. listwise deletion, pairwise deletion, and single imputation procedures) and modern procedures (i.e. multiple imputation and full information maximum likelihood). In the past, several organizations and researchers have warned that traditional missing data techniques (MDTs) can introduce bias into parameter estimates, and can result in a loss of statistical power (e.g., Becker & Powers, 2001; Wilkinson & the APA Task Force on Statistical Inference, 1999). However, previous research has shown …