Please use this identifier to cite or link to this item:

Effect of dichotomizing a continuous variable on linear regression

Authors Ho, Wai Lung
Issue Date 2010
Summary For analyzing the data in applied research studies, continuous exposure variables are frequently partitioned into categorical variables with two levels and those categorized exposure variables is fitted in the regression model and it is called dichotomization. The dichotomization of independent variable will result in the bias on the regression coefficient and a considerable loss of information and power. Furthermore, measurement error is also a serious problem in various scientific areas. Both measurement error and dichotomization can lead to considerable loss of information, power and relative efficiency. In this thesis, we adopts the hypothesis testing on the association between response and exposures with a specified power at fixed significance level in the linear regression model in which the explanatory exposures are subject to measurement error, dichotomization or both.
Note Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2010
Language English
Format Thesis
Access View full-text via DOI
Files in this item:
File Description Size Format
th_redirect.html 337 B HTML
Copyrighted to the author. Reproduction is prohibited without the author’s prior written consent.