Diagnostic tests for bias of estimating equations in weighted regression with missing covariates

DOI10.2307/3316075zbMath0974.62040OpenAlexW2144050607MaRDI QIDQ2747875

Suojin Wang, S.-Y. Claire Lei

Publication date: 16 December 2001

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3316075

zbMATH Keywords

simulationsmissing dataestimating equationsweighted regressionsemiparametric test

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) Parametric hypothesis testing (62F03)

Related Items (2)

Semiparametric approach for non‐monotone missing covariates in a parametric regression model ⋮ A Model Validation Procedure when Covariate Data are Missing at Random

Cites Work

• Tobit models: A survey
• Diagnostic Plots for Missing Data in Least Squares Regression
• A Test of the Missing Data Mechanism for Repeated Categorical Data
• A test of the missing data mechanism for repeated measures data
• Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
• Weighted Semiparametric Estimation in Regression Analysis With Missing Covariate Data
• Adjusting for Nonignorable Drop-Out Using Semiparametric Nonresponse Models

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