Random weighting approximation for Tobit regression models with longitudinal data

DOI10.1016/j.csda.2014.05.020zbMath1506.62195OpenAlexW2089651735MaRDI QIDQ1623677

Y. Aharonov

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2014.05.020

zbMATH Keywords

longitudinal datarandom weightingM-test statisticTobit response

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10)

Related Items (5)

Tobit regression model with parameters of increasing dimensions ⋮ Maximum likelihood estimation for bivariate SUR Tobit modeling in presence of two right-censored dependent variables ⋮ Random weighting method for M-test in linear model with dependent errors ⋮ Least product relative error estimation ⋮ A threshold longitudinal Tobit quantile regression model for identification of treatment‐sensitive subgroups based on interval‐bounded longitudinal measurements and a continuous covariate

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• Analysis of least absolute deviation
• Mixed Effects Models with Censored Data with Application to HIV RNA Levels
• Semiparametric Time-Varying Coefficients Regression Model for Longitudinal Data

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