Handling missing data in modelling quality of clinician-prescribed routine care: sensitivity analysis of departure from missing at random assumption
Missing information is a major drawback in analyzing data collected in many routine health care settings. Multiple imputation assuming a missing at random mechanism is a popular method to handle missing data. The missing at random assumption cannot be confirmed from the observed data alone, hence th...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
SAGE Publications
2020
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