Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change
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Abstract
Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some…
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Keywords
- Confusion
- Scale (ratio)
- Diversity (politics)
- Medicine
- Statistics
- Psychology
- Mathematics
- Sociology
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