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Full-Text Articles in Statistics and Probability
Power And Sample Size Calculations For Interval-Censored Survival Analysis, Hae-Young Kim, John M. Williamson, Hung-Mo Lin
Power And Sample Size Calculations For Interval-Censored Survival Analysis, Hae-Young Kim, John M. Williamson, Hung-Mo Lin
NYMC Faculty Publications
We propose a method for calculating power and sample size for studies involving interval-censored failure time data that only involves standard software required for fitting the appropriate parametric survival model. We use the framework of a longitudinal study where patients are assessed periodically for a response and the only resultant information available to the investigators is the failure window: the time between the last negative and first positive test results. The survival model is fit to an expanded data set using easily computed weights. We illustrate with a Weibull survival model and a two-group comparison. The investigator can specify a …
An Efficient Basket Trial Design, Kristen Cunanan, Alexia Iasonos, Ronglai Shen, Colin B. Begg, Mithat Gonen
An Efficient Basket Trial Design, Kristen Cunanan, Alexia Iasonos, Ronglai Shen, Colin B. Begg, Mithat Gonen
Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series
The landscape for early phase cancer clinical trials is changing dramatically due to the advent of targeted therapy. Increasingly, new drugs are designed to work against a target such as the presence of a specific tumor mutation. Since typically only a small proportion of cancer patients will possess the mutational target, but the mutation is present in many different cancers, a new class of basket trials is emerging, whereby the drug is tested simultaneously in different baskets, i.e., sub-groups of different tumor types. Investigators not only desire to test whether the drug works, but also to determine which types of …
Leveraging Contact Network Structure In The Design Of Cluster Randomized Trials, Guy Harling, Rui Wang, Jukka-Pekka Onnela, Victor Degruttola
Leveraging Contact Network Structure In The Design Of Cluster Randomized Trials, Guy Harling, Rui Wang, Jukka-Pekka Onnela, Victor Degruttola
Harvard University Biostatistics Working Paper Series
Background: In settings like the Ebola epidemic, where proof-of-principle trials have succeeded but questions remain about the effectiveness of different possible modes of implementation, it may be useful to develop trials that not only generate information about intervention effects but also themselves provide public health benefit. Cluster randomized trials are of particular value for infectious disease prevention research by virtue of their ability to capture both direct and indirect effects of intervention; the latter of which depends heavily on the nature of contact networks within and across clusters. By leveraging information about these networks – in particular the degree …