Abstract:
:We describe rank-based approaches to assess principal stratification treatment effects in studies where the outcome of interest is only well-defined in a subgroup selected after randomization. Our methods are sensitivity analyses, in that estimands are identified by fixing a parameter and then we investigate the sensitivity of results by varying this parameter over a range of plausible values. We present three rank-based test statistics and compare their performance through simulations, and provide recommendations. We also study three different bootstrap approaches for determining levels of significance. Finally, we apply our methods to two studies: an HIV vaccine trial and a prostate cancer prevention trial.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Lu X,Mehrotra DV,Shepherd BEdoi
10.1002/sim.5849subject
Has Abstractpub_date
2013-11-20 00:00:00pages
4526-39issue
26eissn
0277-6715issn
1097-0258journal_volume
32pub_type
杂志文章abstract::The problem for assessing biosimilarity and drug interchangeability of follow-on biologics (biosimilar products) is studied. Unlike the generic products, the development of biosimilar products is much more complicated because of fundamental differences in functional structures and manufacturing processes. As a result,...
journal_title:Statistics in medicine
pub_type: 杂志文章
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journal_title:Statistics in medicine
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abstract::Virtually all clinical trials collect multiple endpoints that are usually correlated. Many methods have been proposed to control the family-wise type I error rate (FWER), but these methods often disregard the correlation among the endpoints, such as the commonly used Bonferroni correction, Holm procedure, Wiens' Bonfe...
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journal_title:Statistics in medicine
pub_type: 杂志文章
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journal_title:Statistics in medicine
pub_type: 杂志文章
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journal_title:Statistics in medicine
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pub_type: 临床试验,杂志文章,多中心研究,随机对照试验
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journal_title:Statistics in medicine
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