title: Analysis of hypoglycemic events using negative binomial models.
abstract: Negative binomial regression is a standard model to analyze hypoglycemic events in diabetes clinical trials. Adjusting for baseline covariates could potentially increase the estimation efficiency of negative binomial regression. However, adjusting for covariates raises concerns about model misspecification, in which the negative binomial regression is not robust because of its requirement for strong model assumptions. In some literature, it was suggested to correct the standard error of the maximum likelihood estimator through introducing overdispersion, which can be estimated by the Deviance or Pearson Chi-square. We proposed to conduct the negative binomial regression using Sandwich estimation to calculate the covariance matrix of the parameter estimates together with Pearson overdispersion correction (denoted by NBSP). In this research, we compared several commonly used negative binomial model options with our proposed NBSP. Simulations and real data analyses showed that NBSP is the most robust to model misspecification, and the estimation efficiency will be improved by adjusting for baseline hypoglycemia.
authors.affiliation: Department of Global Statistical Science, Lilly Corporate Center, Eli Lilly and Company, Indianapolis, Indiana 46285, USA. luoju@lilly.com
authors.forename: Junxiang
authors.initials: J
authors.lastname: Luo
authors.forename: Yongming
authors.initials: Y
authors.lastname: Qu
mesh_terms: D016010:Binomial Distribution; D016009:Chi-Square Distribution; D002986:Clinical Trials as Topic / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D003920:Diabetes Mellitus / Q000188:drug therapy; D006801:Humans; D007003:Hypoglycemia / Q000139:chemically induced*; D007004:Hypoglycemic Agents / Q000633:toxicity*; D016013:Likelihood Functions; D015233:Models, Statistical; D012044:Regression Analysis
chemical_list: D007004:Hypoglycemic Agents
keywords: hypoglycemia; negative binomial; overdispersion