Application of a Variable Importance Measure Method

Birkner Merrill D. and J. van der Laan Mark
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Birkner Merrill D.: University of California, Berkeley
J. van der Laan Mark: Division of Biostatistics, School of Public Health, University of California, Berkeley

The International Journal of Biostatistics, 2006, vol. 2, issue 1, 24

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.

Keywords: variable importance; HIV (search for similar items in EconPapers)
Date: 2006
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DOI: 10.2202/1557-4679.1013

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