Term of Award
Spring 2020
Degree Name
Doctor of Public Health in Biostatistics (Dr.P.H.)
Document Type and Release Option
Dissertation (open access)
Copyright Statement / License for Reuse
This work is licensed under a Creative Commons Attribution 4.0 License.
Department
Department of Biostatistics (COPH)
Committee Chair
Lili Yu
Committee Member 1
JIngjing Yin
Committee Member 2
Jun Liu
Abstract
The misclassification simulation extrapolation (MC-SIMEX) method proposed by Küchenho et al. is a general method of handling categorical data with measurement error. It consists of two steps, the simulation and extrapolation steps. In the simulation step, it simulates observations with varying degrees of measurement error. Then parameter estimators for varying degrees of measurement error are obtained based on these observations. In the extrapolation step, it uses a parametric extrapolation function to obtain the parameter estimators for data with no measurement error. However, as shown in many studies, the parameter estimators are still biased as a result of the parametric extrapolation function used in the MC-SIMEX method. Therefore, we propose a nonparametric MC-SIMEX method in which we use a nonparametric extrapolation function. It uses the fractional polynomial method with cross-validation to choose the appropriate fractional polynomial terms. An example is provided based on data from the National Health and Nutrition Examination Survey.
Recommended Citation
Liu, Congjian, "Nonparametric Misclassification Simulation and Extrapolation Method and Its Application" (2020). Electronic Theses and Dissertations. 2043.
https://digitalcommons.georgiasouthern.edu/etd/2043
Research Data and Supplementary Material
No
