title: Bivariate logistic regression: modelling the association of small for gestational age births in twin gestations.
abstract: Clustered binary responses, such as disease status in twins, frequently arise in perinatal health and other epidemiologic applications. The scientific objective involves modelling both the marginal mean responses, such as the probability of disease, and the within-cluster association of the multivariate responses. In this regard, bivariate logistic regression is a useful procedure with advantages that include (i) a single maximization of the joint probability distribution of the bivariate binary responses, and (ii) modelling the odds ratio describing the pairwise association between the two binary responses in relation to several covariates. In addition, since the form of the joint distribution of the bivariate binary responses is assumed known, parameters for the regression model can be estimated by the method of maximum likelihood. Hence, statistical inferences may be based on likelihood ratio tests and profile likelihood confidence intervals. We apply bivariate logistic regression to a perinatal database comprising 924 twin foetuses resulting from 462 pregnancies to model obstetric and clinical risk factors for the association of small for gestational age births in twin gestations.
authors.affiliation: Department of Obstetrics, Gynecology and Reproductive Sciences, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, 125 Paterson St, New Brunswick, NJ 08901-1977, USA. ananthcv@EPI.UMDNJ.EDU
authors.forename: C V
authors.initials: CV
authors.lastname: Ananth
authors.forename: J S
authors.initials: JS
authors.lastname: Preisser
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D016000:Cluster Analysis; D015331:Cohort Studies; D016001:Confidence Intervals; D005260:Female; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D007236:Infant, Small for Gestational Age; D016013:Likelihood Functions; D016015:Logistic Models; D008297:Male; D008423:Maternal Age; D008954:Models, Biological; D015337:Multicenter Studies as Topic; D015999:Multivariate Analysis; D016017:Odds Ratio; D010298:Parity; D011247:Pregnancy; D012737:Sex Factors; D012907:Smoking; D018433:Twin Studies as Topic; D014427:Twins / Q000706:statistics & numerical data*