Article first published online: 4 SEP 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 32, Issue 14, pages 2467–2478, 30 June 2013
How to Cite
Fluss, R., Mandel, M., Freedman, L. S., Weiss, I. S., Zohar, A. E., Haklai, Z., Gordon, E.-S. and Simchen, E. (2013), Correction of sampling bias in a cross-sectional study of post-surgical complications. Statist. Med., 32: 2467–2478. doi: 10.1002/sim.5608
- Issue published online: 4 JUN 2013
- Article first published online: 4 SEP 2012
- Manuscript Accepted: 14 AUG 2012
- Manuscript Received: 6 JUN 2011
- length bias;
- weighted analysis;
- post-surgical infections
Cross-sectional designs are often used to monitor the proportion of infections and other post-surgical complications acquired in hospitals. However, conventional methods for estimating incidence proportions when applied to cross-sectional data may provide estimators that are highly biased, as cross-sectional designs tend to include a high proportion of patients with prolonged hospitalization. One common solution is to use sampling weights in the analysis, which adjust for the sampling bias inherent in a cross-sectional design. The current paper describes in detail a method to build weights for a national survey of post-surgical complications conducted in Israel. We use the weights to estimate the probability of surgical site infections following colon resection, and validate the results of the weighted analysis by comparing them with those obtained from a parallel study with a historically prospective design. Copyright © 2012 John Wiley & Sons, Ltd.