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Mixed linear regression model for longitudinal data: application to an unbalanced anthropometric data set

A longitudinal data set is characterized by a time sequence of two or more observations from each individual. In cohort studies, these data are usually not balanced. A data set related to longitudinal height measurements in children of HIV-infected mothers was recorded at the university hospital of the Federal University in Minas Gerais, Brazil. The objective was to assess the application of the mixed effect model to this unbalanced data set. At six months of age, on average boys were 1.8cm taller than girls, and seroreverter infants were 2.9cm taller than their HIV+ peers. At 12 months of age, on average boys were 2.4cm taller than girls and seroreverter children were 3.5cm taller than HIV+ ones. In addition to describing longitudinal height behavior, this model also includes the growth rate estimation for this infant population by gender and group.

Linear Models; Likelihood Functions; Anthropometry; Growth


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