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Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/5134
Title: Sample size calculation for testing an interaction effect in a logistic regression under measurement error model
Authors: Lee, Michelle Oi San
Issue Date: 2003
Abstract: Error in measuring exposure variable is a common concern in all etiologic research. There has been increasing acknowledgment of the importance of measurement error in epidemiology. In addition, binary response arising in many fields of study is common in both biological and social sciences. Much of the recent biostatistical and epidemiological literature has concerned the association between a binary response and exposure. In the epidemiologic studies, calculation of sample size and statistical power are essential ingredients. This Thesis, therefore, adopts a hypothesis testing based on the method of maximum likelihood approach to approximate sample sizes which are needed to test hypothesis on association between a continuous exposure and a categorical variable on a binary outcome variable at a specified significance level and power against given alternatives for a logistic regression model when the explanatory variables are measured with errors.
Description: Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2003
viii, 67 leaves : ill. ; 30 cm
HKUST Call Number: Thesis MATH 2003 Lee
URI: http://hdl.handle.net/1783.1/5134
Appears in Collections:MATH Master Theses

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