Pairwise joint modeling of clustered and high-dimensional outcomes with covariate missingness in pediatric pneumonia care
Multiple outcomes reflecting different aspects of routine care are a common phenomenon in health care research. A common approach of handling such outcomes is multiple univariate analyses, an approach which does not allow for answering research questions pertaining to joint inference. In this study,...
मुख्य लेखकों: | Gachau, S, Njagi, EN, Molenberghs, G, Owuor, N, Sarguta, R, English, M, Ayieko, P |
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स्वरूप: | Journal article |
भाषा: | English |
प्रकाशित: |
Wiley
2022
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समान संसाधन
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Analysis of hierarchical routine data with covariate missingness: effects of audit and feedback on clinicians' prescribed pediatric pneumonia care in Kenyan hospitals
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Analysis of Hierarchical Routine Data With Covariate Missingness: Effects of Audit & Feedback on Clinicians' Prescribed Pediatric Pneumonia Care in Kenyan Hospitals
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प्रकाशित: (2019-07-01) -
Handling missing data in a composite outcome with partially observed components: simulation study based on clustered paediatric routine data
द्वारा: Gachau, S, और अन्य
प्रकाशित: (2021) -
Handling missing data in modelling quality of clinician-prescribed routine care: sensitivity analysis of departure from missing at random assumption
द्वारा: Gachau, S, और अन्य
प्रकाशित: (2020) -
Comparison of methods for handling covariate missingness in propensity score estimation with a binary exposure
द्वारा: Donna L. Coffman, और अन्य
प्रकाशित: (2020-06-01)