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Inverse Intensity Weighting in Generalized Linear Models as an Option for Analyzing Longitudinal Data with Triggered Observations

Longitudinal epidemiologic studies with irregularly observed categorical outcomes present considerable analytical challenges. Generalized linear models (GLMs) tolerate without bias only values missing completely at random and assume that all observations contribute equally. A triggered sampling stud...

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Autors principals: Van Ness, Peter H., Allore, Heather G., Fried, Terri R., Lin, Haiqun
Format: Artigo
Idioma:Inglês
Publicat: Oxford University Press 2010
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Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC2800302/
https://ncbi.nlm.nih.gov/pubmed/19942574
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/aje/kwp333
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