Analyzing multiply matched cohort studies with two different comparison groups: application to pregnancy rates among HIV+ women

Biometrics. 2003 Sep;59(3):632-9. doi: 10.1111/1541-0420.00073.


We develop a new statistical method to analyze multiply matched cohort studies with two different comparison groups. We employ a linear-logistic model to describe the underlying log-odds ratios and use a conditional likelihood approach to conduct inference. Under the assumption of homogeneous log-odds ratios, we provide methods to construct both asymptotic and exact confidence regions of the two log-odds ratios in a simple case. We propose a score test to evaluate the assumption of homogeneous log-odds ratios across strata. While our methods are general, we develop them around a specific application, namely, the study of pregnancy rates in HIV-infected women. Our analyses suggest that HIV infection is associated with a decrease in pregnancy rates and that this decrease in fertility becomes significant after accounting for illicit drug use.

Publication types

  • Comparative Study

MeSH terms

  • Biometry
  • Cohort Studies
  • Connecticut / epidemiology
  • Female
  • HIV Infections / complications*
  • HIV Infections / epidemiology*
  • Humans
  • Likelihood Functions
  • Linear Models
  • Models, Statistical
  • Pregnancy
  • Pregnancy Complications, Infectious / epidemiology*
  • Substance-Related Disorders / complications