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Discrete Choice Models for Nonmonotone Nonignorable Missing Data: Identification and Inference
Nonmonotone missing data arise routinely in empirical studies of social and health sciences, and when ignored, can induce selection bias and loss of efficiency. In practice, it is common to account for nonresponse under a missing-at-random assumption which although convenient, is rarely appropriate...
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| Опубликовано в: : | Stat Sin |
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| Главные авторы: | , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2018
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8118571/ https://ncbi.nlm.nih.gov/pubmed/33994754 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.5705/ss.202016.0325 |
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