Publication Date


Document Type


First Advisor

Ryu, Duchwan

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Statistics and Actuarial Science


Most of statistical theory operates under the assumption that the true values of covariates have been measured correctly, but it is not always possible to obtain the true values of these covariates. A common issue, specifically in regression models, is that predictors are misclassified or measured with systematic measurement error. There have been many methods developed for handling measurement error, specifically in the case where measurement error is nondifferential, where the measurement error can be treated as independent from the covariates. The frequentist method known as simulation extrapolation (SIMEX) is one of these methods that specifically handles the case for recovering a regression's slope coefficient from a naively calculated estimate. We examined the case where there is some correlation between the covariates and the measurement error itself, and we made the adjustments necessary to develop a SIMEX method for differential measurement error.


29 pages




Northern Illinois University

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