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Application of a Variable Importance Measure Method

Author

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  • Birkner Merrill D.

    (University of California, Berkeley)

  • van der Laan Mark J.

    (Division of Biostatistics, School of Public Health, University of California, Berkeley)

Abstract

Van der Laan (2005) proposed a targeted method used to construct variable importance measures coupled with respective statistical inference. This technique involves determining the importance of a variable in predicting an outcome. This method can be applied as inverse probability of treatment weighted (IPTW) or double robust inverse probability of treatment weighted (DR-IPTW) estimators. The variance and respective p-value of the estimate are calculated by estimating the influence curve. This article applies the Van der Laan (2005) variable importance measures and corresponding inference to HIV-1 sequence data. In this application, the method is targeted at every codon position. In this data application, protease and reverse transcriptase codon positions on the HIV-1 strand are assessed to determine their respective variable importance, with respect to an outcome of viral replication capacity. We estimate the DR-IPTW W-adjusted variable importance measure for a specified set of potential effect modifiers W. In addition, simulations were performed on two separate datasets to examine the DR-IPTW estimator.

Suggested Citation

  • Birkner Merrill D. & van der Laan Mark J., 2006. "Application of a Variable Importance Measure Method," The International Journal of Biostatistics, De Gruyter, vol. 2(1), pages 1-24, July.
    • Handle: RePEc:bpj:ijbist:v:2:y:2006:i:1:n:6
    DOI: 10.2202/1557-4679.1013
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    Keywords

    variable importance; HIV;

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