Measuring morbidity: Disease counts, binary variables, and statistical power

Kenneth F. Ferraro, Janet M. Wilmoth

Research output: Contribution to journalArticlepeer-review

58 Scopus citations


Objectives. This study compares the use of the 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 if statistical power is adequate for the binary variable approach. Methods. Morbidity measures from adults in 2 large national surveys were used in both cross sectional and longitudinal analyses. Results. Although differences across the approaches are modest, the binary variable approach offers greater explanatory power and slightly higher R2 values. Despite these advantages, statistical power is insufficient in some cases, especially for conditions that are relatively rare and/or that manifest modest differences on the outcome variable. Discussion. 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 nonserious conditions should be more useful in many research projects while avoiding the risk of inadequate statistical power.

Original languageEnglish (US)
Pages (from-to)S173-S189
JournalJournals of Gerontology - Series B Psychological Sciences and Social Sciences
Issue number3
StatePublished - May 2000
Externally publishedYes

ASJC Scopus subject areas

  • Health(social science)
  • Sociology and Political Science
  • Life-span and Life-course Studies


Dive into the research topics of 'Measuring morbidity: Disease counts, binary variables, and statistical power'. Together they form a unique fingerprint.

Cite this