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Centre for Policy on Ageing | |
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Measuring morbidity
— disease counts, binary variables, and statistical power | | Author(s) | Kenneth F Ferraro, Janet M Wilmoth |
| Journal title | Journals of Gerontology: Series B, Psychological Sciences and Social Sciences, vol 55B, no 3, May 2000 |
| Pages | pp S173-S189 |
| Keywords | Ill health ; Diseases ; Statistics ; United States of America. |
| Annotation | This study compares the use of binary disease variables with counts of the same conditions in models of self-rated health, to better understand the advantages and disadvantages of each approach. In particular, the analysis seeks to determine whether statistical power is adequate for the binary variable approach. Morbidity measures from adults in two large US surveys were used in both cross-sectional and longitudinal analyses. Although differences across the approaches are modest, the binary variable approach offers greater power and slightly higher R squared values. Despite these advantages, statistical power is insufficient in some cases, especially for conditions that are relatively rare and/or manifest modest differences on the outcome variable. Statistical power estimates are advisable when using the binary variable approach, especially if the list of diseases and health conditions is extensive. Although a simple count of diseases may be useful in some research applications, separate counts for serious and non-serious conditions should be more useful in many research projects while avoiding the risk of inadequate statistical power. (RH). |
| Accession Number | CPA-000825233 A |
| Classmark | CH: CJ: 3Y: 7T |
Data © Centre for Policy on Ageing |
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| ...from the Ageinfo database published by Centre for Policy on Ageing. |
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