Document Detail


Power analyses for negative binomial models with application to multiple sclerosis clinical trials.
MedLine Citation:
PMID:  22251172     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
We use negative binomial (NB) models for the magnetic resonance imaging (MRI)-based brain lesion count data from parallel group (PG) and baseline versus treatment (BVT) trials for relapsing remitting multiple sclerosis (RRMS) patients, and describe the associated likelihood ratio (LR), score, and Wald tests. We perform power analyses and sample size estimation using the simulated percentiles of the exact distribution of the test statistics for the PG and BVT trials. When compared to the corresponding nonparametric test, the LR test results in 30-45% reduction in sample sizes for the PG trials and 25-60% reduction for the BVT trials.
Authors:
Mallik Rettiganti; H N Nagaraja
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of biopharmaceutical statistics     Volume:  22     ISSN:  1520-5711     ISO Abbreviation:  J Biopharm Stat     Publication Date:  2012 Mar 
Date Detail:
Created Date:  2012-01-18     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9200436     Medline TA:  J Biopharm Stat     Country:  England    
Other Details:
Languages:  eng     Pagination:  237-59     Citation Subset:  IM    
Affiliation:
a Department of Statistics , The Ohio State University , Columbus , Ohio , USA.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Simultaneous generation of binary and normal data with specified marginal and association structures...
Next Document:  Sample Size Calculation Through the Incorporation of Heteroscedasticity and Dependence for a Penaliz...