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Inferences on relative failure rates in stratified mark‐specific proportional hazards models with missing marks, with application to human immunodeficiency virus vaccine efficacy trials
Author(s) -
Gilbert Peter B.,
Sun Yanqing
Publication year - 2015
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/rssc.12067
Subject(s) - estimator , human immunodeficiency virus (hiv) , statistics , robustness (evolution) , missing data , hiv vaccine , vaccine efficacy , vaccine trial , mathematics , statistical hypothesis testing , sequence (biology) , sample size determination , econometrics , medicine , virology , biology , vaccination , genetics , gene , biochemistry
Summary The paper develops hypothesis testing procedures for the stratified mark‐specific proportional hazards model in the presence of missing marks. The motivating application is preventive human immunodeficiency virus (HIV) vaccine efficacy trials, where the mark is the genetic distance of an infecting HIV sequence to an HIV sequence represented inside the vaccine. The test statistics are constructed on the basis of two‐stage efficient estimators, which utilize auxiliary predictors of the missing marks. The asymptotic properties and finite sample performances of the testing procedures are investigated, demonstrating double robustness and effectiveness of the predictive auxiliaries to recover efficiency. The methods are applied to the RV144 vaccine trial.