Correction of sampling bias in a cross-sectional study of post-surgical complications.

Abstract:

: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.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Fluss R,Mandel M,Freedman LS,Weiss IS,Zohar AE,Haklai Z,Gordon ES,Simchen E

doi

10.1002/sim.5608

subject

Has Abstract

pub_date

2013-06-30 00:00:00

pages

2467-78

issue

14

eissn

0277-6715

issn

1097-0258

journal_volume

32

pub_type

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