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Handling Missing Values in Interrupted Time Series Analysis of Longitudinal Individual-Level Data
BACKGROUND: In the interrupted time series (ITS) approach, it is common to average the outcome of interest at each time point and then perform a segmented regression (SR) analysis. In this study, we illustrate that such ‘aggregate-level’ analysis is biased when data are missing at random (MAR) and p...
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| Publicado no: | Clin Epidemiol |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Dove
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7549500/ https://ncbi.nlm.nih.gov/pubmed/33116899 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.2147/CLEP.S266428 |
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