| Literature DB >> 24038204 |
Abstract
Negative binomial model has been increasingly used to model the count data in recent clinical trials. It is frequently chosen over Poisson model in cases of overdispersed count data that are commonly seen in clinical trials. One of the challenges of applying negative binomial model in clinical trial design is the sample size estimation. In practice, simulation methods have been frequently used for sample size estimation. In this paper, an explicit formula is developed to calculate sample size based on the negative binomial model. Depending on different approaches to estimate the variance under null hypothesis, three variations of the sample size formula are proposed and discussed. Important characteristics of the formula include its accuracy and its ability to explicitly incorporate dispersion parameter and exposure time. The performance of the formula with each variation is assessed using simulations.Keywords: count data; negative binomial model; power analysis; sample size calculation
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Year: 2013 PMID: 24038204 DOI: 10.1002/sim.5947
Source DB: PubMed Journal: Stat Med ISSN: 0277-6715 Impact factor: 2.373