Model selection criterion for causal parameters in structural mean models based on a quasi-likelihood

DOI10.1111/BIOM.12165zbMath1299.62034OpenAlexW1932914422WikidataQ44879267 ScholiaQ44879267MaRDI QIDQ2927630

Yutaka Matsuyama, Yasuo Ohashi, Masataka Taguri

Publication date: 4 November 2014

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/biom.12165

zbMATH Keywords

instrumental variablemodel selectionquasi-likelihoodAkaike's information criterioncausal inferencestructural mean modelsnon-complianceeffect modificationG-estimation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (2)

Hybrid reliability analysis with uncertain statistical variables, sparse variables and interval variables ⋮ Model assessment in dynamic treatment regimen estimation via double robustness

Cites Work

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• Numerical Methods for Nonlinear Estimating Equations
• Correcting for non-compliance in randomized trials using structural nested mean models
• Structural mean models for compliance analysis in randomized clinical trials and the impact of errors on measures of exposure

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