A small sample study of the STEPP approach to assessing treatment-covariate interactions in survival data
Statistics in Medicine, ISSN: 0277-6715, Vol: 28, Issue: 8, Page: 1255-1268
2009
- 40Citations
- 28Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations40
- Citation Indexes40
- 40
- CrossRef37
- Captures28
- Readers28
- 28
Article Description
A new, intuitive method has recently been proposed to explore treatment-covariate interactions in survival data arising from two treatment arms of a clinical trial. The method is based on constructing overlapping subpopulations of patients with respect to one (or more) covariates of interest and in observing the pattern of the treatment effects estimated across the subpopulations. A plot of these treatment effects is called a subpopulation treatment effect pattern plot. Here, we explore the small sample characteristics of the asymptotic results associated with the method and develop an alternative permutation distribution-based approach to inference that should be preferred for smaller sample sizes. We then describe an extension of the method to the case in which the pattern of estimated quantiles of survivor functions is of interest. Copyright © 2009 John Wiley & Sons, Ltd.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=65649108011&origin=inward; http://dx.doi.org/10.1002/sim.3524; http://www.ncbi.nlm.nih.gov/pubmed/19170050; https://onlinelibrary.wiley.com/doi/10.1002/sim.3524; http://doi.wiley.com/10.1002/sim.3524; http://onlinelibrary.wiley.com/doi/10.1002/sim.3524/abstract
Wiley
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