Application of a Variable Importance Measure Method to HIV-1 Sequence Data
Download the Paper Forward to a colleague
Abstract:
van der Laan (2005) proposed a method to construct variable importance measures and provided the respective statistical inference. This technique involves determining the importance of a variable in predicting an outcome. This method can be applied as an inverse probability of treatment weighted (IPTW) or double robust inverse probability of treatment weighted (DR-IPTW) estimator. A respective significance of the estimator is determined by estimating the influence curve and hence determining the corresponding variance and p-value. This article applies the van der Laan (2005) variable importance measures and corresponding inference to HIV-1 sequence data. In this data application, protease and reverse transcriptase codon position 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 W-adjusted variable importance measure for a specified set of potential effect modifiers W. Both the IPTW and DR-IPTW methods were implemented on this dataset
Subject Area:
General Biostatistics, Multivariate Analysis
Suggested Citation:
Merrill D. Birkner and Mark J. van der Laan, "Application of a Variable Importance Measure Method to HIV-1 Sequence Data" (November 2005). U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 196.
http://www.bepress.com/ucbbiostat/paper196