@article {1561,
	title = {Analyzing multiply matched cohort studies with two different comparison groups: application to pregnancy rates among HIV+ women.},
	journal = {Biometrics},
	volume = {59},
	year = {2003},
	month = {2003 Sep},
	pages = {632-9},
	abstract = {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.},
	keywords = {Biometry, Cohort Studies, Connecticut, Female, HIV Infections, Humans, Likelihood Functions, Linear Models, Models, Statistical, Pregnancy, Pregnancy Complications, Infectious, Substance-Related Disorders},
	issn = {0006-341X},
	author = {Li, Yan and Zelterman, Daniel and Forsyth, Brian W C}
}
