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Epidemiology Commons

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Theses and Dissertations

Public health

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Full-Text Articles in Epidemiology

Diagnostics And Model Selection For Generalized Linear Models And Generalized Estimating Equations, Chelsea Boquet Deroche May 2015

Diagnostics And Model Selection For Generalized Linear Models And Generalized Estimating Equations, Chelsea Boquet Deroche

Theses and Dissertations

The use of generalized linear models and generalized estimating equations in the public health and medical fields are important tools for research, specifically for modeling clinical trials, evaluating preventive measures, and secondary data analysis. It is important for these researchers to have the necessary tools to analyze and model their data correctly. This dissertation focuses on a penalized maximum likelihood estimation method for generalized linear models, measures of association such as the coefficient of determination and R2 for generalized estimating equations, and a modified quasi-likelihood information criterion for generalized estimation equations.

Common problems that arise during estimation of generalized …


Association Between Breastfeeding And Infant Growth: A Probable Reverse Causality, Shraddha Vyas Jan 2013

Association Between Breastfeeding And Infant Growth: A Probable Reverse Causality, Shraddha Vyas

Theses and Dissertations

Background: Much conflicting results exist in the association between breastfeeding and infant growth. One of these confusions is related to the temporal sequence between breastfeeding practice and infant growth.

Objective: This study aimed at examining the association and investigating a possible reverse causality between breastfeeding and infant growth.

Method: Infant Feeding Practices Survey II, a national longitudinal database with repeated measurements, following women prenatally and until one year postpartum (N=2914) was used. Mixed linear model assessed the impact of breastfeeding from the 2nd, 4th, 6th and 9th months on infant growth at the 3rd, 5th, 7th and 12th months, respectively. …