A semi-parametric quantile regression approach to zero-inflated and incomplete longitudinal outcomes

DOI10.1007/s10182-020-00362-9zbMath1457.62107OpenAlexW3010372196MaRDI QIDQ2218562

Pulak Ghosh, Jayabrata Biswas, Kiranmoy Das

Publication date: 15 January 2021

Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10182-020-00362-9

zbMATH Keywords

probit modelmissing datahealth insurancejoint quantile modelsvarying coefficients modelszero-inflated longitudinal data

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Missing data (62D10)

Related Items (3)

A semi-parametric Bayesian dynamic hurdle model with an application to the health and retirement study ⋮ A Bayesian variable selection approach to longitudinal quantile regression ⋮ A Bayesian quantile regression approach to multivariate semi-continuous longitudinal data

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