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An application of analyzing correlated binary outcomes in a study of twins

Vo, Hai (2016) An application of analyzing correlated binary outcomes in a study of twins. Master's Thesis, University of Pittsburgh. (Unpublished)

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Twin studies have been an important area of epidemiologic research. Traditional analyses of risk use regular linear or logistic models. Regular linear regression and logistic regression assume that all observations are independent of each other. However, there is correlation between the observations in a study of twins that needs to be taken into account. Two ways to handle the correlated binary outcomes include Generalized Estimating Equations (GEE) and mixed models. In this thesis, we used univariate and multivariable GEE models to investigate an association between maternal pre-pregnancy BMI and a binary outcome variable, small for gestational age (SGA) in twins. In addition, we used splines to explore the relationship between SGA and pre-pregnancy BMI. SGA birth outcomes are considered one of the major concerns in public health issues because they could affect infant mortality as well as infant morbidity. Our data is a random sample of birth certificate records of twin births in Pennsylvania from 2003 to 2011 (n=20,072 infants). Our findings suggest that underweight women have higher risk of SGA births compared to normal weight women controlling for other maternal characteristics (OR=1.62, 95% CI (1.33,1.99)). The public health significance of this work is that the results from this paper could be used as a reference for making decisions on interventions to reduce SGA births in twins.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Vo, Haihtv1@pitt.eduHTV1
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairYouk, Ada O.ayouk@pitt.eduAYOUK
Committee CoChairBuchanich, Jeanine Mjeanine@pitt.eduJEANINE
Committee MemberBodnar, Lisa M.bodnar@edc.pitt.eduBODNAR
Centers: University Centers > University Center for Social and Urban Research
Date: 30 March 2016
Date Type: Submission
Defense Date: 13 April 2016
Approval Date: 29 June 2016
Submission Date: 26 April 2016
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 62
Institution: University of Pittsburgh
Schools and Programs: School of Public Health > Biostatistics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: No
Uncontrolled Keywords: correlated binary outcomes, GEE, small for gestational age, spline, mixed models, twins, pre-pregnancy BMI
Date Deposited: 29 Jun 2016 18:48
Last Modified: 15 Nov 2016 14:32


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