Skip Navigation


American Journal of Epidemiology Advance Access originally published online on October 7, 2009
American Journal of Epidemiology 2009 170(10):1307-1315; doi:10.1093/aje/kwp265
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
170/10/1307    most recent
kwp265v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Shrier, I.
Right arrow Articles by Rich, B.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Shrier, I.
Right arrow Articles by Rich, B.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

American Journal of Epidemiology © The Author 2009. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

PRACTICE OF EPIDEMIOLOGY

Analyses of Injury Count Data: Some Do's and Don'ts

Ian Shrier*, Russell J. Steele, James Hanley and Benjamin Rich

* Correspondence to Dr. Ian Shrier, Centre for Clinical Epidemiology and Community Studies, SMBD-Jewish General Hospital, 3755 Cote Sainte Catherine Road, Montreal, Quebec H3T 1E2, Canada (e-mail: ian.shrier{at}mcgill.ca).

Received for publication April 16, 2009. Accepted for publication August 5, 2009.

The analysis of injury data requires different considerations from the analysis of other types of outcomes because an individual can experience the outcome many times. When describing injury patterns using numerator-only data (e.g., proportion of upper-extremity injuries vs. lower-extremity injuries), simple comparisons of proportions are inappropriate because 1) individuals are compared with themselves and 2) multiple testing increases the potential for incorrect inference. Bootstrapping (resampling) techniques can be used to determine confidence intervals and whether the frequencies significantly differ across categories. When describing injury rates, the authors suggest plotting the observed injury rate against the number of exposures to obtain a visual representation of the heterogeneity of risk across individuals. Because the distribution of injury rates is often skewed, some research questions may be best addressed by comparing the weighted median injury rates instead of the weighted mean injury rates (which are given by standard formulae). Again, resampling techniques can be used to obtain a null distribution for injury rates in order to determine whether there are subjects who have unexpectedly high injury rates. More advanced analyses are required to account for multiplicity.

bootstrap; bootstrap confidence interval; epidemiologic methods; heterogeneity; population characteristics; statistics; wounds and injuries


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.