Combined analysis of matched and unmatched case-control studies: Comparison of risk estimates from different studies

Victor Moreno, Miguel L. Martín, F. Xavier Bosch, Silvia De Sanjosé, Ferran Torres, Nubia Muñoz

Research output: Contribution to journalReview articleResearchpeer-review

17 Citations (Scopus)


The authors propose a method to perform a combined analysis of matched and unmatched case-control studies that is based on an adaptation of logistic regression and can be performed using standard software. This methodology can be used to do pooled analyses of studies with different designs. Likelihood ratio tests can be performed to assess association, heterogeneity, or trend. The standard errors of the coefficients allow the derivation of a Wald test and the calculation of confidence intervals. Another application is to compare relative risk estimators for the same risk factors studied in different phases of a disease in an effort to explore factors that may be more important in one phase than in another. Interaction terms of risk factors with variables that code the different pooled studies can be used for this purpose. The advantage of using this method is that a formal statistical comparison can be performed in which the regression coefficients of the interaction terms estimate the relative differences in risk (odds ratio ratios) between the studies. This estimation can be adjusted for other confounder factors. Two examples of application using data from case-control studies on cervical cancer and colorectal cancer are presented to illustrate the use of this epidemiologic method.
Original languageEnglish
Pages (from-to)293-299
JournalAmerican Journal of Epidemiology
Issue number3
Publication statusPublished - 1 Feb 1996


  • Epidemiologic methods
  • Interaction
  • Matching
  • Regression analysis
  • Retrospective studies
  • Risk assessment
  • Statistics


Dive into the research topics of 'Combined analysis of matched and unmatched case-control studies: Comparison of risk estimates from different studies'. Together they form a unique fingerprint.

Cite this