This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Roth, P. L. Articles by Switzer, D. M. Search for Related Content Social Bookmarking                         What's this?

Missing Data in Multiple Item Scales: A Monte Carlo Analysis of Missing Data Techniques

Fred S. Switzer, III

Deborah M. Switzer

Clemson University

Researchers in many fields use multiple item scales to measure important variables such as attitudes and personality traits, but find that some respondents failed to complete certain items. Past missing data research focuses on missing entire instruments, and is of limited help because there are few variables to help impute missing scores and the variables are often not highly related to each other. Multiple item scales offer the unique opportunity to impute missing values from other correlated items designed to measure the same construct. A Monte Carlo analysis was conducted to compare several missing data techniques. The techniques included listwise deletion, regression imputation, hot-deck imputation, and two forms of mean substitution. Results suggest that regression imputation and substituting the mean response of a person to other items on a scale are very promising approaches. Furthermore, the imputation techniques often outperformed listwise deletion.

Organizational Research Methods, Vol. 2, No. 3, 211-232 (1999)
DOI: 10.1177/109442819923001


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?

This article has been cited by other articles:

				J. Gooty, M. Gavin, P. D. Johnson, M. L. Frazier, and D. B. Snow In the Eyes of the Beholder: Transformational Leadership, Positive Psychological Capital, and Performance Journal of Leadership and Organizational Studies, May 1, 2009; 15(4): 353 - 367. [Abstract] [PDF]

				D. A. Newman and H.-P. Sin How Do Missing Data Bias Estimates of Within-Group Agreement? Sensitivity of SD WG, CVWG, rWG(J), rWG(J) * , and ICC to Systematic Nonresponse Organizational Research Methods, January 1, 2009; 12(1): 113 - 147. [Abstract] [PDF]

				J. C. Spilsbury, K. E. Fletcher, R. Creeden, and S. Friedman Psychometric Properties of the Dimensions of Stressful Events Rating Scale Traumatology, December 1, 2008; 14(4): 116 - 130. [Abstract] [PDF]

				M. Fichman and J. N. Cummings Multiple Imputation for Missing Data: Making the most of What you Know Organizational Research Methods, July 1, 2003; 6(3): 282 - 308. [Abstract] [PDF]

				R. A. Mcdonald, P. W. Thurston, and M. R. Nelson A Monte Carlo Study of Missing Item Methods Organizational Research Methods, January 1, 2000; 3(1): 71 - 92. [Abstract] [PDF]