Goodness-of-fit tests for general linear models with covariates missed at random

DOI10.1016/J.JSPI.2012.02.039zbMath1237.62054OpenAlexW2001255640MaRDI QIDQ419330

Xu Guo, Wang-li Xu

Publication date: 18 May 2012

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2012.02.039

zbMATH Keywords

inverse probability weightslack of fit testrandomly missing covariates

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20)

Related Items (10)

Dimension reduction with missing response at random ⋮ Nonlinear interaction detection through partial dimension reduction with missing response data ⋮ Estimation and test procedures for composite quantile regression with covariates missing at random ⋮ Weighted local linear CQR for varying-coefficient models with missing covariates ⋮ Goodness of fit test for general linear model with nonignorable missing on response variable ⋮ Penalized weighted composite quantile regression for partially linear varying coefficient models with missing covariates ⋮ Dimension reduction estimation for central mean subspace with missing multivariate response ⋮ Model checks for nonparametric regression with missing data: a comparative study ⋮ Model checking for parametric regressions with response missing at random ⋮ Consistent model checking procedures for parametric regressions with missing response

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• Asymptotic Properties of Non-Linear Least Squares Estimators
• An Estimated Likelihood Method for Continuous Outcome Regression Models With Outcome-Dependent Sampling

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