DeepAI AI Chat
Log In Sign Up

Bayesian Ordinal Quantile Regression with a Partially Collapsed Gibbs Sampler

11/16/2019
by   Isabella N Grabski, et al.
0

Unlike standard linear regression, quantile regression captures the relationship between covariates and the conditional response distribution as a whole, rather than only the relationship between covariates and the expected value of the conditional response. However, while there are well-established quantile regression methods for continuous variables and some forms of discrete data, there is no widely accepted method for ordinal variables, despite their importance in many medical contexts. In this work, we describe two existing ordinal quantile regression methods and demonstrate their weaknesses. We then propose a new method, Bayesian ordinal quantile regression with a partially collapsed Gibbs sampler (BORPS). We show superior results using BORPS versus existing methods on an extensive set of simulations. We further illustrate the benefits of our method by applying BORPS to the Fragile Families and Child Wellbeing Study data to tease apart associations with early puberty among both genders. Software is available at: GitHub.com/igrabski/borps.

READ FULL TEXT

page 7

page 8

page 9

page 10

page 11

page 13

09/29/2022

Bayesian Quantile Regression for Ordinal Models

The paper introduces a Bayesian estimation method for quantile regressio...
09/28/2021

bqror: An R package for Bayesian Quantile Regression in Ordinal Models

This article describes an R package bqror that estimates Bayesian quanti...
06/01/2020

Quantile regression for compositional covariates

Quantile regression is a very important tool to explore the relationship...
12/25/2010

Ordinal Risk-Group Classification

Most classification methods provide either a prediction of class members...
07/23/2018

Prediction based on conditional distributions of vine copulas

Vine copula models are a flexible tool in multivariate non-Gaussian dist...
10/14/2022

Individualized Inference in Bayesian Quantile Directed Acyclic Graphical Models

We propose an approach termed "qDAGx" for Bayesian covariate-dependent q...
10/16/2020

Quantile regression with ReLU Networks: Estimators and minimax rates

Quantile regression is the task of estimating a specified percentile res...