Case Study in Imputation and Data Reduction

  • Frank E. HarrellJr.
Part of the Springer Series in Statistics book series (SSS)

Abstract

The following case study illustrates these techniques:
  1. 1.

    missing data imputation using mean substitution, recursive partitioning, and customized regressions;

     
  2. 2.

    variable clustering;

     
  3. 3.

    data reduction using principal components analysis and pretransformations;

     
  4. 4.

    restricted cubic spline fitting using ordinary least squares, in the context of scaling; and

     
  5. 5.

    scaling/variable transformations using canonical variates and nonparametric additive regression.

     

Keywords

Primary Biliary Cirrhosis Data Reduction Multiple Imputation Canonical Variate Variable Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Frank E. HarrellJr.
    • 1
  1. 1.Department of BiostatisticsVanderbilt University School of MedicineNashvilleUSA

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