%0 Journal Article
%J Biometrics
%D 2003
%T Analyzing multiply matched cohort studies with two different comparison groups: application to pregnancy rates among HIV+ women.
%A Li, Yan
%A Zelterman, Daniel
%A Forsyth, Brian W C
%K Biometry
%K Cohort Studies
%K Connecticut
%K Female
%K HIV Infections
%K Humans
%K Likelihood Functions
%K Linear Models
%K Models, Statistical
%K Pregnancy
%K Pregnancy Complications, Infectious
%K Substance-Related Disorders
%N 3
%P 632-9
%V 59
%X 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.
%8 2003 Sep