M.S. (Master of Science)
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.
Partipilo, Dominic, "The Simulation Extrapolation Method with Differential Measurement Error" (2021). Graduate Research Theses & Dissertations. 7529.
Northern Illinois University
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