A Bayesian approach for misclassified ordinal response data
DOI10.1080/02664763.2019.1582613OpenAlexW2916437452MaRDI QIDQ5034149
Timothy Mutsvari, Lizbeth Naranjo, Jacinto Martín, Emmanuel Lesaffre, Carlos J. Pérez
Publication date: 24 February 2022
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02664763.2019.1582613
Bayesian analysisMarkov chain Monte Carlo methodsdata augmentationmisclassificationordinal regression model
Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Linear inference, regression (62J99) Applications of statistics (62Pxx)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Modeling individual migraine severity with autoregressive ordered probit models
- Bayesian analysis of multivariate probit models with surrogate outcome data
- Bayesian analysis of correlated misclassified binary data
- A Bayesian analysis of the multinomial probit model with fully identified parameters
- Power prior distributions for generalized linear models
- Analysis of ordered probit model with surrogate response data and measurement error in covariates
- Threshold Model for Misclassified Binary Responses with Applications to Animal Breeding
- Binomial Regression with Misclassification
- Bayesian Statistical Modelling
- Measurement Error
- Ordinal Data Modeling
- A New Perspective on Priors for Generalized Linear Models
- Modeling Repeated Measures With Monotonic Ordinal Responses and Misclassification, With Applications to Studying Maturation
- Bayesian identifiability and misclassification in multinomial data
- Bayesian Measures of Model Complexity and Fit
- Binary Regression with Misclassified Response and Covariate Subject to Measurement Error: a Bayesian Approach
- Analysis of Misclassified Correlated Binary Data Using a Multivariate Probit Model when Covariates are Subject to Measurement Error
- Addressing misclassification for binary data: probit and t-link regressions
- Bayesian Analysis of Binary and Polychotomous Response Data
- Bayesian Models for Categorical Data
- Measurement Error in Nonlinear Models
- A Bayesian Ordinal Logistic Regression Model to Correct for Interobserver Measurement Error in a Geographical Oral Health Study
This page was built for publication: A Bayesian approach for misclassified ordinal response data