A study on the type I error rate and power for generalized linear mixed model containing one random effect

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dc.contributor.author Wang, Yu
dc.date.accessioned 2017-04-05T15:10:54Z
dc.date.available 2017-04-05T15:10:54Z
dc.date.issued 2017-05-01 en_US
dc.identifier.uri http://hdl.handle.net/2097/35301
dc.description.abstract In animal health research, it is quite common for a clinical trial to be designed to demonstrate the efficacy of a new drug where a binary response variable is measured on an individual experimental animal (i.e., the observational unit). However, the investigational treatments are applied to groups of animals instead of an individual animal. This means the experimental unit is the group of animals and the response variable could be modeled with the binomial distribution. Also, the responses of animals within the same experimental unit may then be statistically dependent on each other. The usual logit model for a binary response assumes that all observations are independent. In this report, a logit model with a random error term representing the group of animals is considered. This is model belongs to a class of models referred to as generalized linear mixed models and is commonly fit using the SAS System procedure PROC GLIMMIX. Furthermore, practitioners often adjust the denominator degrees of freedom of the test statistic produced by PROC GLIMMIX using one of several different methods. In this report, a simulation study was performed over a variety of different parameter settings to compare the effects on the type I error rate and power of two methods for adjusting the denominator degrees of freedom, namely “DDFM = KENWARDROGER” and “DDFM = NONE”. Despite its reputation for fine performance in linear mixed models with normally distributed errors, the “DDFM = KENWARDROGER” option tended to perform poorly more often than the “DDFM = NONE” option in the logistic regression model with one random effect. en_US
dc.language.iso en en_US
dc.publisher Kansas State University en
dc.subject Binomial Response en_US
dc.subject Generalized Linear Mixed Model en_US
dc.subject KENWARDROGER en_US
dc.subject Type I Error en_US
dc.subject Power en_US
dc.title A study on the type I error rate and power for generalized linear mixed model containing one random effect en_US
dc.type Report en_US
dc.description.degree Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Statistics en_US
dc.description.advisor Christopher Vahl en_US
dc.date.published 2017 en_US
dc.date.graduationmonth May en_US

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