A mixed model approach for intent-to-treat analysis in longitudinal clinical trials with missing values
Missing values and dropouts are common issues in longitudinal studies in all areas of medicine and public health. Intent-to-treat (ITT) analysis has become a widely accepted method for the analysis of controlled clinical trials. We performed a detailed investigation based on simulation studies to de...
| Main Authors: | , |
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| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Research Triangle Park, NC
RTI Press
March 2009, 2009
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| Series: | Methods report
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| Subjects: | |
| Online Access: | |
| Collection: | National Center for Biotechnology Information - Collection details see MPG.ReNa |
| Summary: | Missing values and dropouts are common issues in longitudinal studies in all areas of medicine and public health. Intent-to-treat (ITT) analysis has become a widely accepted method for the analysis of controlled clinical trials. We performed a detailed investigation based on simulation studies to develop recommendations for this situation. We compared sizes (type I errors) and power between some popular ad hoc approaches and the linear mixed model approach under different missing value scenarios. Our results suggest that, for studies with a high percentage of missing values, the mixed model approach without any ad hoc imputation is more powerful than other options |
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| Item Description: | "RTI Press publication MR-0009-0903." |
| Physical Description: | 1 PDF file (9 pages) illustrations |