Bias study of the naive estimator in a longitudinal binary mixed-effects model with measurement error and misclassification in covariates.

Dankwa, Ernest (2014) Bias study of the naive estimator in a longitudinal binary mixed-effects model with measurement error and misclassification in covariates. Masters thesis, Memorial University of Newfoundland.

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Abstract

When covariates in Longitudinal data are subject to errors, the naive estimates of the model parameters are often biased. In this research, we exploit a Dynamic Binary Mixed-effects Model using a Generalized Quasi-likelihood approach. Through simulations, we shall study the patterns in the bias of the naive estimator of the parameters that ignores the errors in the covariates.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/8082
Item ID: 8082
Additional Information: Includes bibliographical references (pages 106-108).
Department(s): Science, Faculty of > Mathematics and Statistics
Date: August 2014
Date Type: Submission
Library of Congress Subject Heading: Analysis of covariance; Estimation theory; Longitudinal method; Generalized estimating equations

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