Modeling Adverse Birth Outcomes via Confirmatory Factor Quantile Regression

DOI10.1111/j.1541-0420.2011.01639.xzbMath1241.62150OpenAlexW2015205870WikidataQ51556163 ScholiaQ51556163MaRDI QIDQ2893987

Lane F. Burgette, Jerome P. Reiter

Publication date: 27 June 2012

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2011.01639.x

zbMATH Keywords

Bayesian inferenceGibbs samplingbirth weight

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)

Related Items (6)

Multilevel quantile function modeling with application to birth outcomes ⋮ Bayesian model selection in ordinal quantile regression ⋮ Bayesian tobit quantile regression with penalty ⋮ Variable selection in quantile regression via Gibbs sampling ⋮ Nonparametric confidence intervals for quantiles with randomized nomination sampling ⋮ factorQR

Uses Software

• R
• quantreg

Cites Work

• An integrative analysis of cancer gene expression studies using Bayesian latent factor modeling
• Regression Quantiles
• Reappraising Medfly Longevity
• Bayesian Smoothing and Regression Splines for Measurement Error Problems
• Approximate Bayesian inference for quantiles
• Bayesian Analysis of Binary and Polychotomous Response Data
• Panel Data Models With Interactive Fixed Effects
• Bayesian exponentially tilted empirical likelihood
• A Bayesian Nonparametric Approach to Inference for Quantile Regression
• Parameterization and Bayesian Modeling
• Structural Equation Modeling
• Bayesian quantile regression
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