Download or read book Covariate Measurement Error in Logistic Regression written by L. A. Stefanski and published by . This book was released on 1985 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a logistic regression model when covariates are subject to measurement error the naive estimator, obtained by regressing on the observed covariates, is asymptotically biased. This document introduces a bias-adjusted estimator and two estimators appropriate for normally distributed measurement errors; a functional maximum likelihood estimator and an estimator which exploits the consequences of sufficiency. The four proposals are studied asymptotically under conditions which are appropriate when the measurement error is small. A small Monte-Carlo study illustrates the superiority of the measurement-error estimators in certain situations. Additional keywords: mathematical models.
Download or read book Logistic Regression with Misclassified Response and Covariate Measurement Error written by Anna E. McGlothlin and published by . This book was released on 2007 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a variety of regression applications, measurement problems are unavoidable because infallible measurement tools may be expensive or unavailable. When modeling the relationship between a response variable and covariates, we must account for the uncertainty that is inherently introduced when one or both of these variables are measured with error. In this dissertation, we explore the consequences of and remedies for imperfect measurements. We consider a Bayesian analysis for modeling a binary outcome that is subject to misclassification. We investigate the use of informative conditional means priors for the regression coefficients. Additionally, we incorporate random effects into the model to accommodate correlated responses. Markov chain Monte Carlo methods are utilized to perform the necessary computations. We use the deviance information criterion to aid in model selection. Next, we consider data where measurements are flawed for both the response and explanatory variables. Our interest is in the case of a misclassified dichotomous response and a continuous covariate that is unobservable, but where measurements are available on its surrogate. A logistic regression model is developed to incorporate the measurement error in the covariate as well as the misclassification in the response. The methods developed are illustrated through an example. Results from a simulation experiment are provided illustrating advantages of the approach. Finally, we expand this model to incorporate random effects, resulting in a generalized linear mixed model for a misclassified response and covariate measurement error. We demonstrate the use of this model using a simulated data set.
Download or read book Measurement Error Covariate Models in Logistic Regression written by Donald Dah-Shyong Jiang and published by . This book was released on 1994 with total page 710 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dealing with Measurement Error in Covariates with Special Reference to Logistic Regression Model a Flexible Parametric Approach written by and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In many fields of statistical application the fundamental task is to quantify the association between some explanatory variables or covariates and a response or outcome variable through a suitable regression model. The accuracy of such quantification depends on how precisely we measure the relevant covariates. In many instances, we can not measure some of the covariates accurately, rather we can measure noisy versions of them. In statistical terminology this is known as measurement errors or errors in variables. Regression analyses based on noisy covariate measurements lead to biased and inaccurate inference about the true underlying response-covariate associations. In this thesis we investigate some aspects of measurement error modelling in the case of binary logistic regression models. We suggest a flexible parametric approach for adjusting the measurement error bias while estimating the response-covariate relationship through logistic regression model. We investigate the performance of the proposed flexible parametric approach in comparison with the other flexible parametric and nonparametric approaches through extensive simulation studies. We also compare the proposed method with the other competitive methods with respect to a real-life data set. Though emphasis is put on the logistic regression model the proposed method is applicable to the other members of the generalized linear models, and other types of non-linear regression models too. Finally, we develop a new computational technique to approximate the large sample bias that my arise due to exposure model misspecification in the estimation of the regression parameters in a measurement error scenario.
Download or read book Logistic Regression with Covariate Measurement Error in an Adaptive Design written by JoAnna Christine Crixell and published by . This book was released on 2008 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive designs are increasingly popular in clinical trials. This is because such designs have the potential to decrease patient exposure to treatments that areless efficacious or unsafe. The Bayesian approach to adaptive designs is attractivebecause it makes systematic use of prior data and other information in a way that is consistent with the laws of probability. The goal of this dissertation is to examine the effects of measurement error on a Bayesian adaptive design. Measurement error problems are common in a variety of regression applications where the variable of interest cannot be measured perfectly. This is often unavoidable because infallible measurement tools to account for such error are either too expensive or unavailable. When modeling the relationship between a response variable and other covariates, we must account for any uncertainty introduced when one or both of these variables are measured with error. This dissertation will explore the consequence of imperfect measurements on a Bayesian adaptive design.
Download or read book Measurement Error in Nonlinear Models written by Raymond J. Carroll and published by CRC Press. This book was released on 2006-06-21 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and ex
Download or read book Covariate Dichotomization Measurement Error in Logistic Regression written by Seth Matthew Thompson and published by . This book was released on 1995 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parameter Estimation for the Logistic Regression Model with Errors in Covariate written by Huyen D. Nguyen and published by . This book was released on 2021 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a logistic regression model, when the covariate is measured with error, the estimators of the regression coefficient parameters can be biased. We propose a method for estimating parameters of a logistic regression with case-control data, when the covariate is subject to measurement error. The density of the covariate is estimated by using the deconvolution kernel density estimation. The parameters of the regression are estimated by the integrated squared distance based on the log ratio of the estimated density. We show the consistency and the asymptotic normality of the proposed estimators. Simulation study shows the superiority of the proposed method in different sample sizes and measurement error magnitudes scenario. The methodology is applied to estimating the relationship of systolic blood pressure and the presence of coronary heart disease.
Download or read book Resampling Approach for Estimating Prediction Error and for Adjusting Logistic Regression Models for Covariate Measurement Error written by Wei Li and published by . This book was released on 2002 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Analysis of Measurement Error Models and Applications written by Philip J. Brown and published by American Mathematical Soc.. This book was released on 1990 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measurement error models describe functional relationships among variables observed, subject to random errors of measurement. This book treats general aspects of the measurement problem and features a discussion of the history of measurement error models.
Download or read book Linear and Logistic Regression with Measurement Erro and Misclassification in Covariates written by Hok Laam Cheng and published by . This book was released on 2020 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Measurement Error written by John P. Buonaccorsi and published by CRC Press. This book was released on 2010-03-02 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illu
Download or read book Measurement Error in Logistic Regression by Discriminant Analysis with Applications to the Epidemiology of Coronary Heart Disease written by Richard David Bawol and published by . This book was released on 1979 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Asymptotic Properties of Log Odds Ratio Regression Estimators with Sparse Strata and Covariate Measurement Error written by Andrew Benjamin Forbes and published by . This book was released on 1990 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Influence and Measurement Error in Logistic Regression written by Leonard A. Stefanski and published by . This book was released on 1983 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Measurement Error in Logistic Regression Model written by Sau Yee Lo and published by . This book was released on 2004 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Aspects of Misspecification in Statistical Models written by Wenxin Jiang and published by . This book was released on 1996 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt:
