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Survival analysis with time varying covariates measured at random times by design
Author(s) -
Rathbun Stephen L.,
Song Xiao,
Neustifter Benjamin,
Shiffman Saul
Publication year - 2013
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/j.1467-9876.2012.01064.x
Subject(s) - covariate , statistics , survival analysis , random effects model , mathematics , computer science , medicine , meta analysis
Summary. Ecological momentary assessment is a method for collecting realtime data in subjects' environments. It often uses electronic devices to obtain information on psychological state through administration of questionnaires at times that are selected from a probability‐based sampling design. This information can be used to model the effect of momentary variation in psychological state on the lifetimes to events such as smoking lapse. Motivated by this, a probability sampling framework is proposed for estimating the effect of time varying covariates on the lifetimes to events. Presented as an alternative to joint modelling of the covariate process as well as event lifetimes, this framework calls for sampling covariates at the event lifetimes and at times that are selected according to a probability‐based sampling design. A design‐unbiased estimator for the cumulative hazard is substituted into the log‐likelihood, and the resulting objective function is maximized to obtain the proposed estimator. This estimator has two quantifiable sources of variation: that due to the survival model and that due to sampling the covariates. Data from a nicotine patch trial are used to illustrate the approach proposed.