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On Inverse Probability Weighting for Nonmonotone Missing at Random Data
The development of coherent missing data models to account for nonmonotone missing at random (MAR) data by inverse probability weighting (IPW) remains to date largely unresolved. As a consequence, IPW has essentially been restricted for use only in monotone missing data settings. We propose a class...
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| Publicado no: | J Am Stat Assoc |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6051732/ https://ncbi.nlm.nih.gov/pubmed/30034062 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2016.1256814 |
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