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Sample size calculation for studies with grouped survival data.

dc.contributor.author Li, Zhiguo
dc.contributor.author Owzar, Kouros
dc.contributor.author Wang, Xiaofei
dc.contributor.author Wu, Yuan
dc.date.accessioned 2018-07-01T14:27:46Z
dc.date.available 2018-07-01T14:27:46Z
dc.date.issued 2018-06-10
dc.identifier.issn 0277-6715
dc.identifier.issn 1097-0258
dc.identifier.uri https://hdl.handle.net/10161/17196
dc.description.abstract Grouped survival data arise often in studies where the disease status is assessed at regular visits to clinic. The time to the event of interest can only be determined to be between two adjacent visits or is right censored at one visit. In data analysis, replacing the survival time with the endpoint or midpoint of the grouping interval leads to biased estimators of the effect size in group comparisons. Prentice and Gloeckler developed a maximum likelihood estimator for the proportional hazards model with grouped survival data and the method has been widely applied. Previous work on sample size calculation for designing studies with grouped data is based on either the exponential distribution assumption or the approximation of variance under the alternative with variance under the null. Motivated by studies in HIV trials, cancer trials and in vitro experiments to study drug toxicity, we develop a sample size formula for studies with grouped survival endpoints that use the method of Prentice and Gloeckler for comparing two arms under the proportional hazards assumption. We do not impose any distributional assumptions, nor do we use any approximation of variance of the test statistic. The sample size formula only requires estimates of the hazard ratio and survival probabilities of the event time of interest and the censoring time at the endpoints of the grouping intervals for one of the two arms. The formula is shown to perform well in a simulation study and its application is illustrated in the three motivating examples.
dc.language eng
dc.relation.ispartof Statistics in medicine
dc.relation.isversionof 10.1002/sim.7847
dc.subject grouped survival data
dc.subject proportional hazards model
dc.subject sample size calculation
dc.title Sample size calculation for studies with grouped survival data.
dc.type Journal article
dc.date.updated 2018-07-01T14:27:44Z
pubs.organisational-group School of Medicine
pubs.organisational-group Duke
pubs.organisational-group Duke Cancer Institute
pubs.organisational-group Institutes and Centers
pubs.organisational-group Biostatistics & Bioinformatics
pubs.organisational-group Basic Science Departments
pubs.publication-status Published


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