|Title||Sample size determination in shared frailty models for multivariate time-to-event data.|
|Publication Type||Journal Article|
|Year of Publication||2014|
|Authors||Chen, Liddy M., Joseph G. Ibrahim, and Haitao Chu|
|Journal||J Biopharm Stat|
|Keywords||Data Interpretation, Statistical, Humans, Multivariate Analysis, Sample Size, Time Factors|
The frailty model is increasingly popular for analyzing multivariate time-to-event data. The most common model is the shared frailty model. Although study design consideration is as important as analysis strategies, sample size determination methodology in studies with multivariate time-to-event data is greatly lacking in the literature. In this article, we develop a sample size determination method for the shared frailty model to investigate the treatment effect on multivariate event times. We analyzed the data using both a parametric model and a piecewise model with unknown baseline hazard, and compare the empirical power with the calculated power. Last, we discuss the formula for testing the treatment effect on recurrent events.
|Alternate Journal||J Biopharm Stat|
|Original Publication||Sample size determination in shared frailty models for multivariate time-to-event data.|
|PubMed Central ID||PMC4024091|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
U54-MD008620 / MD / NIMHD NIH HHS / United States
1P01CA142538 / CA / NCI NIH HHS / United States
2P30CA077598 / CA / NCI NIH HHS / United States
Sample size determination in shared frailty models for multivariate time-to-event data.