Measuring morbidity: disease counts, binary variables, and statistical power.

TitleMeasuring morbidity: disease counts, binary variables, and statistical power.
Publication TypeJournal Article
Year of Publication2000
AuthorsFerraro, KF, Wilmoth, JM
JournalJ Gerontol B Psychol Sci Soc Sci
Volume55
Issue3
PaginationS173-89
Date Published2000 May
ISSN Number1079-5014
Call Numberpubs_2000_ferraro_morbidity.pdf
KeywordsAdult, Aged, Chronic disease, Cross-Sectional Studies, Female, Geriatric Assessment, Health Surveys, Humans, Longitudinal Studies, Male, Middle Aged, Models, Statistical, United States
Abstract

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.

DOI10.1093/geronb/55.3.s173
User Guide Notes

http://www.ncbi.nlm.nih.gov/pubmed/11833985?dopt=Abstract

Endnote Keywords

Disease/Morbidity/Subjective Probabilities

Endnote ID

15030

Alternate JournalJ Gerontol B Psychol Sci Soc Sci
Citation Key6722
PubMed ID11833985
Grant ListAG11705 / AG / NIA NIH HHS / United States
AG13739 / AG / NIA NIH HHS / United States