A comparative study on estimation methods to deal with the endogeneity in linear random-intercept models with an extension

DOI10.1080/00949655.2016.1196689zbMath1492.62123OpenAlexW2438005998MaRDI QIDQ5106767

Geert Verbeke, Iraj Kazemi, Reyhaneh Rikhtehgaran

Publication date: 22 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1942/22836

zbMATH Keywords

longitudinal dataendogenous covariatesfixed-effect approachmixture strategyrandom-effect approach

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Linear inference, regression (62J99)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Large Sample Properties of Generalized Method of Moments Estimators
• Multivariate regression models for panel data
• The effect of misspecifying the random-effects distribution in linear mixed models for longitudinal data
• The incidental parameter problem since 1948
• Analysis of Panel Data
• Prediction of Random Effects in Linear and Generalized Linear Models under Model Misspecification
• A Linear Mixed-Effects Model With Heterogeneity in the Random-Effects Population
• Separating Between- and Within-Cluster Covariate Effects by Using Conditional and Partitioning Methods
• Panel Data and Unobservable Individual Effects
• On the Pooling of Time Series and Cross Section Data
• Between- and Within-Cluster Covariate Effects in the Analysis of Clustered Data
• An instrumental variable random‐coefficients model for binary outcomes
• Microeconometrics
• Regression methods in biostatistics. Linear, logistic, survival, and repeated measures models.

This page was built for publication: A comparative study on estimation methods to deal with the endogeneity in linear random-intercept models with an extension