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A dynamic approach for reconstructing missing longitudinal data using the linear increments model

Missing observations are commonplace in longitudinal data. We discuss how to model and analyze such data in a dynamic framework, that is, taking into consideration the time structure of the process and the influence of the past on the present and future responses. An autoregressive model is used as...

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Autori principali: Aalen, Odd O., Gunnes, Nina
Natura: Artigo
Lingua:Inglês
Pubblicazione: Oxford University Press 2010
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Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC3293429/
https://ncbi.nlm.nih.gov/pubmed/20388914
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/biostatistics/kxq014
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