Analyzing data in which the outcome is time to an event part II: The presence of multiple covariates.
In this article, the second of a series on the analysis of time to event data, we address the case in which multiple predictors (covariates) that may influence the time to an event are taken into account. The hazard function is introduced, and is given in a form useful for assessing the impact of multiple covariates on time to an event. Methods for the assessment of model fitting are also discussed and an example with cancer survival as outcome with the presence or absence of multiple genes as covariates is presented.
Mera
Robertino
R
LSU Health Sciences Center, New Orleans, LA 70112, USA. robertino.m.mera@sb.com
Thompson
Hilary W
HW
Prasad
Chandan
C
D006801:Humans; D018895:Microsatellite Repeats; D017063:Outcome Assessment, Health Care; D016016:Proportional Hazards Models; D013223:Statistics as Topic; D013274:Stomach Neoplasms / Q000235:genetics / Q000401:mortality; D015996:Survival Rate; D013997:Time Factors