Handling Item-Level Missing Data

Mike C. Parent

doi:10.1177/0011000012445176

journal article May 10, 2012

Handling Item-Level Missing Data

Mike C. Parent

The Counseling Psychologist Vol. 41 No. 4 pp. 568-600 · SAGE Publications

View at Publisher Save 10.1177/0011000012445176

Abstract

The topic of missing data has been receiving increasing attention, with calls to apply advanced methods of handling missingness to counseling psychology research. The present study sought to assess whether advanced methods of handling item-level missing data performed equivalently to simpler methods in designs similar to those counseling psychologists typically engage in. Results of an initial preliminary analysis, an analysis using real-world data, and a series of simulation studies were used in the present investigation. Results indicated that available case analysis, mean substitution, and multiple imputation had similar results across low levels of missing data, though in data with higher levels of missing data and other problems (e.g., small sample size or scales with weak internal reliability) mean substitution produced inflation of correlation coefficients among items. The present results support the use of available case analysis when dealing with low-level item-level missingness.

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Details

Published: May 10, 2012
Vol/Issue: 41(4)
Pages: 568-600
License: View

Authors

M

Mike C. Parent

University of Florida, Gainesville, FL, USA

Cite This Article

Mike C. Parent (2012). Handling Item-Level Missing Data. The Counseling Psychologist, 41(4), 568-600. https://doi.org/10.1177/0011000012445176

Handling Item-Level Missing Data

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