Add to ORKGSummary. The paper focuses on a Bayesian treatment of measurement error problems and on the question of the specification of the prior distribution of the unknown covariates. It presents a flexible semiparametric model for this distribution based on a mixture of normal distributions with an unknownumber of components. Implementation of this prior model as part of a full Bayesian analysis of measurement error problems is described in classical set-ups that are encountered in epidemiological studies: logistic regression between unknown covariates and outcome, with a normal or log-normal error model and a validation group. The feasibility of this combined model is tested and its performance is demonstrated in a simulation study that includes a...
In many epidemiological studies it is common to resort to regression models relating incidence of a ...
Background: In epidemiological studies explanatory variables are frequently subject...
Although the literature on measurement error problems is quite extensive, solutions to even the most...
The paper focuses on a Bayesian treatment of measurement error problems and on the question of the s...
A mixture measurement error model built upon skew normal distributions and normal distributions is d...
This work presents a Bayesian semiparametric approach for dealing with regression models where the c...
AbstractThis work presents a Bayesian semiparametric approach for dealing with regression models whe...
A mixture measurement error model built upon skew normal distributions and normal distributions is d...
Thesis (Ph.D.)--University of Rochester. School of Medicine & Dentistry. Dept. of Biostatistics and ...
© 2014, The International Biometric Society. We consider the problem of robust estimation of the reg...
The class of normal mean-variance mixture (NMVM) distributions is a rich family of asymmetric and he...
<div><p>We consider the problem of estimating the density of a random variable when precise measurem...
Includes bibliographical references (p. 96-98).In a variety of regression applications, measurement ...
In many fields of statistical application the fundamental task is to quantify the association betwee...
Summary. We construct Bayesian methods for semiparametric modeling of a monotonic regression func-ti...
In many epidemiological studies it is common to resort to regression models relating incidence of a ...
Background: In epidemiological studies explanatory variables are frequently subject...
Although the literature on measurement error problems is quite extensive, solutions to even the most...
The paper focuses on a Bayesian treatment of measurement error problems and on the question of the s...
A mixture measurement error model built upon skew normal distributions and normal distributions is d...
This work presents a Bayesian semiparametric approach for dealing with regression models where the c...
AbstractThis work presents a Bayesian semiparametric approach for dealing with regression models whe...
A mixture measurement error model built upon skew normal distributions and normal distributions is d...
Thesis (Ph.D.)--University of Rochester. School of Medicine & Dentistry. Dept. of Biostatistics and ...
© 2014, The International Biometric Society. We consider the problem of robust estimation of the reg...
The class of normal mean-variance mixture (NMVM) distributions is a rich family of asymmetric and he...
<div><p>We consider the problem of estimating the density of a random variable when precise measurem...
Includes bibliographical references (p. 96-98).In a variety of regression applications, measurement ...
In many fields of statistical application the fundamental task is to quantify the association betwee...
Summary. We construct Bayesian methods for semiparametric modeling of a monotonic regression func-ti...
In many epidemiological studies it is common to resort to regression models relating incidence of a ...
Background: In epidemiological studies explanatory variables are frequently subject...
Although the literature on measurement error problems is quite extensive, solutions to even the most...