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Semiparametric regression models and sensitivity analysis of longitudinal data with nonrandom dropouts

We propose a family of regression models to adjust for nonrandom dropouts in the analysis of longitudinal outcomes with fully observed covariates. The approach conceptually focuses on generalized linear models with random effects. A novel formulation of a shared random effects model is presented and...

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Autori principali: Todem, David, Kim, KyungMann, Fine, Jason, Peng, Limin
Natura: Artigo
Lingua:Inglês
Pubblicazione: 2010
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Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC3023945/
https://ncbi.nlm.nih.gov/pubmed/21258610
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/j.1467-9574.2009.00435.x
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