Hostname: page-component-7bb8b95d7b-pwrkn Total loading time: 0 Render date: 2024-09-11T11:12:43.303Z Has data issue: false hasContentIssue false
  • English
  • Français

Analysis of Matched Samples

Published online by Cambridge University Press:  21 June 2016

Robert F. Woolson  and
Louise-Anne McNutt
Robert F. Woolson*
Affiliation:
Division of Biostatistics, Department of Preventive Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa
Louise-Anne McNutt
Affiliation:
Division of Biostatistics, Department of Preventive Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa
*
Division of Biostatistics, 28IIA Steindler Bldg, University of Iowa Hospitals and Clinics, Iowa City, IA 52242
Get access Rights & Permissions [Opens in a new window]

Extract

Introduction in order to study the association between disease status (eg, nosocomial infection) and some exposure variable (eg, number of days on urinary catheter), it is often necessary to take into account other variables that may influence either the disease status or the exposure variable. For example, Freeman et al described a retrospective (in their terminology “case-referent”) study of a neonatal population. In this study, cases of nosocomial infection are selected in addition to corresponding control individuals who did not experience a nosocomial infection. All patients were selected from a neonatal intensive care unit, and the goal was to study the role of umbilical artery catheterization and its association with nosocomial infection. As noted by Freeman et al, this is a complex question because the risk of nosocomial infection might reasonably depend not only on the duration of catheterization, but also on the birth weight of the infant.

Type
Special Sections
Information
Infection Control & Hospital Epidemiology , Volume 10 , Issue 3 , March 1989 , pp. 123 - 126
Copyright
Copyright © The Society for Healthcare Epidemiology of America 1989

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Freeman, J, Goldmann, D, JE, McGowan Jr: Confounding and the analysis of multiple variables in hospital epidemiologs. Infect Control 1987; 8:465–473.Google Scholar
2. McNutt, I-A, Woolson, R: Statistical analysis of 2×2 tables, infect Control Hosp Epidemiol 1988; 9:420–423.10.2307/30144310CrossRefGoogle Scholar
3. Breslow, N, Day, N: Statistical Methods in Cancer Research: The Analysis of Case-Control Studies. World Health Organization, Scientific Publication #32, Lyon, 1980.Google ScholarPubMed
4. McNemar, Q: Note on the sampling error of the difference between correlated proportions or percentages. Psychomctrika 1947; 12:153–157.10.1007/BF02295996Google Scholar
5. RF, Woolson: Statistical Methods for the Analysis of Biomedical Data, New York, Wiley & Sons, Inc, 1987.Google Scholar
6. Schlesselman, J: Case-control Studies: Design, Conduct and Analysis. New York, Oxford University Press, 1982.Google Scholar
7. HK, Ury: Efficiency of case-control studies with multiple controls per case: Continuous or dichotomous data. Biometrics 1975; 31:643–649.Google Scholar
8. Mantel, N, Haenszel, W: Statistical aspects of the analysis of data from retrospective studies of disease. Journal of the National Cancer Institute 1959; 22:719–748.Google Scholar