Abstract
In this chapter, I provide step-by-step instructions for performing multiple imputation with Schafer’s (1997) NORM 2.03 program. Although these instructions apply most directly to NORM, most of the concepts apply to other MI programs as well.
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References
Graham, J. W., Cumsille, P. E., & Elek-Fisk, E. (2003). Methods for handling missing data. In J. A. Schinka & W. F. Velicer (Eds.). Research Methods in Psychology (pp. 87–114). Volume 2 of Handbook of Psychology (I. B. Weiner, Editor-in-Chief). New York: John Wiley & Sons.
Graham, J. W., & Donaldson, S. I. (1993). Evaluating interventions with differential attrition: The importance of nonresponse mechanisms and use of followup data. Journal of Applied Psychology, 78, 119–128.
Graham, J. W., & Hofer, S. M. (1992). EMCOV User’s Manual. Unpublished manuscript, University of Southern California.
Graham, J. W., & Hofer, S. M. (2000). Multiple imputation in multivariate research. In T. D. Little, K. U. Schnabel, & J. Baumert, (Eds.), Modeling longitudinal and multiple-group data: Practical issues, applied approaches, and specific examples. (pp. 201–218). Hillsdale, NJ: Erlbaum.
Graham, J. W., Taylor, B. J., Olchowski, A. E., & Cumsille, P. E. (2006). Planned missing data designs in psychological research. Psychological Methods, 11, 323–343.
Hansen, W. B., & Graham, J. W. (1991). Preventing alcohol, marijuana, and cigarette use among adolescents: Peer pressure resistance training versus establishing conservative norms. Preventive Medicine, 20, 414–430.
Harel, O. (2007). Inferences on missing information under multiple imputation and two-stage multiple imputation. Statistical Methodology, 4, 75–89.
Harel, O. (2003). Strategies For Data Analysis With Two Types Of Missing Values. Technical Report, The Methodology Center, The Pennsylvania State University.
Price, B. (1977). Ridge regression: Application to nonexperimental data. Psychological Bulletin, 84, 759–766.
Schafer, J. L. (1997). Analysis of Incomplete Multivariate Data. New York: Chapman and Hall.
Schafer, J. L., and Olsen, M. K. (1998). Multiple imputation for multivariate missing data Âproblems: A data analyst’s perspective. Multivariate Behavioral Research, 33, 545–571.
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Graham, J.W. (2012). Multiple Imputation with Norm 2.03. In: Missing Data. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4018-5_3
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DOI: https://doi.org/10.1007/978-1-4614-4018-5_3
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