title: The analysis of the influence of birth order and other factors in multiple birth data.
abstract: We compare three methods which can be used to analyse the influence of birth order and other factors on health outcomes in multiple birth data. We consider marginal models based on generalized estimating equations (GEE) and two kinds of conditional models; conditional logistic regression (CLR) and mixed effects models (MEM). Although the models may be written similarly, there are differences in both the interpretation and the numerical values assigned to the parameters. Our main conclusion is that GEE and MEM are preferable to CLR since they provide more flexibility in dealing with missing values and covariates. The choice between GEE and MEM is less obvious and depends on the data, the parameter of interest and statistical power.
authors.affiliation: Department of Statistics, University of Haifa, Mount Carmel, Haifa 31905, Israel. davidov@stat.haifa.ac.il
authors.forename: Ori
authors.initials: O
authors.lastname: Davidov
authors.forename: Havi
authors.initials: H
authors.lastname: Murad
authors.forename: Ayala
authors.initials: A
authors.lastname: Lusky
authors.forename: Eric S
authors.initials: ES
authors.lastname: Shinwell
authors.forename: Brian
authors.initials: B
authors.lastname: Reichman
authors.forename: Laurence
authors.initials: L
authors.lastname: Freedman
mesh_terms: D001722:Birth Order; D005163:Factor Analysis, Statistical; D006801:Humans; D007226:Infant Mortality; D007231:Infant, Newborn; D007557:Israel; D016015:Logistic Models; D009017:Morbidity; D009099:Multiple Birth Offspring / Q000706:statistics & numerical data*; D018433:Twin Studies as Topic