Multiple Imputation with Norm 2.03

  • John W. Graham
Chapter
Part of the Statistics for Social and Behavioral Sciences book series (SSBS)

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.

Keywords

Covariance Autocorrelation Lost Rounded Suffix 

References

  1. 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.Google Scholar
  2. 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.CrossRefGoogle Scholar
  3. Graham, J. W., & Hofer, S. M. (1992). EMCOV User’s Manual. Unpublished manuscript, University of Southern California.Google Scholar
  4. 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.Google Scholar
  5. 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.CrossRefGoogle Scholar
  6. 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.CrossRefGoogle Scholar
  7. Harel, O. (2007). Inferences on missing information under multiple imputation and two-stage multiple imputation. Statistical Methodology, 4, 75–89.MathSciNetMATHCrossRefGoogle Scholar
  8. Harel, O. (2003). Strategies For Data Analysis With Two Types Of Missing Values. Technical Report, The Methodology Center, The Pennsylvania State University.Google Scholar
  9. Price, B. (1977). Ridge regression: Application to nonexperimental data. Psychological Bulletin, 84, 759–766.CrossRefGoogle Scholar
  10. Schafer, J. L. (1997). Analysis of Incomplete Multivariate Data. New York: Chapman and Hall.MATHCrossRefGoogle Scholar
  11. Schafer, J. L., and Olsen, M. K. (1998). Multiple imputation for multivariate missing data ­problems: A data analyst’s perspective. Multivariate Behavioral Research, 33, 545–571.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • John W. Graham
    • 1
  1. 1.Department of Biobehavioral HealthThe Pennsylvania State UniversityUniversity ParkUSA

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