title: A note on calculating asymptotic confidence intervals for the adjusted risk difference and number needed to treat in the Cox regression model.
abstract: Recently, Laubender and Bender (Stat. Med. 2010; 29: 851-859) applied the average risk difference (RD) approach to estimate adjusted RD and corresponding number needed to treat measures in the Cox proportional hazards model. We calculated standard errors and confidence intervals by using bootstrap techniques. In this paper, we develop asymptotic variance estimates of the adjusted RD measures and corresponding asymptotic confidence intervals within the counting process theory and evaluated them in a simulation study. We illustrate the use of the asymptotic confidence intervals by means of data of the Düsseldorf Obesity Mortality Study.
authors.affiliation: German Cancer Consortium (DKTK), Heidelberg, Germany; Institute of Medical Informatics, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-University Munich, Munich, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany.
authors.forename: Ruediger P
authors.initials: RP
authors.lastname: Laubender
authors.forename: Ralf
authors.initials: R
authors.lastname: Bender
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D003198:Computer Simulation; D016001:Confidence Intervals; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000401:mortality; D016016:Proportional Hazards Models; D012306:Risk; D012907:Smoking / Q000401:mortality; D055815:Young Adult
keywords: Cox proportional hazards regression; adjustment; confidence intervals; confounding; counting process; exposure impact number (EIN); number needed to be exposed (NNE); number needed to treat (NNT); risk difference (RD)