On model selection and model misspecification in causal inference

scientific article published on 12 November 2010

On model selection and model misspecification in causal inference is …
instance of (P31):
scholarly articleQ13442814

External links are
P356DOI10.1177/0962280210387717
P698PubMed publication ID21075803
P5875ResearchGate publication ID47791233
P894zbMATH Open document ID1365.62431

P50authorStijn VansteelandtQ37067381
P2093author name stringMaarten Bekaert
Gerda Claeskens
P2860cites workModeling and variable selection in epidemiologic analysisQ24538916
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The effectiveness of right heart catheterization in the initial care of critically ill patients. SUPPORT InvestigatorsQ34734466
Variable selection for propensity score modelsQ34803815
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Bayesian perspectives for epidemiological research. II. Regression analysisQ36747786
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Multiply robust inference for statistical interactions.Q42735809
The impact of confounder selection criteria on effect estimationQ43670469
Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiologyQ43854281
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Semiparametric estimation of treatment effect in a pretest-posttest studyQ44858940
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An application of model-fitting procedures for marginal structural modelsQ46272561
Simulation study of confounder-selection strategies.Q52884423
Confounder Selection in Environmental Epidemiology: Assessment of Health Effects of Prenatal Mercury ExposureQ53470915
The Method of Path CoefficientsQ56341515
The central role of the propensity score in observational studies for causal effectsQ56882400
Local Versus Global Models for Classification ProblemsQ58179916
Analysis of Incomplete Data Using Inverse Probability Weighting and Doubly Robust EstimatorsQ58618847
DiscussionsQ58819127
P433issue1
P921main subjectcausal inferenceQ5054566
P6104maintained by WikiProjectWikiProject MathematicsQ8487137
P304page(s)7-30
P577publication date2010-11-12
P1433published inStatistical Methods in Medical ResearchQ7604374
P1476titleOn model selection and model misspecification in causal inference
P478volume21

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