Open AccessCOMPARING LONGITUDINAL PROFILES BEFORE AND AFTER AN INTERVENTION
Author(s) -
Omar Cléo Neves Pereira,
Márcia Lorena Alves dos Santos,
Tiago Peres da Silva Suguiura,
Beatriz Regina Brum,
Camila Borghi Rodriguero,
Tuane Krupek,
Sueli Mutsumi Tsukuda Ichisato,
Roberto Barbosa Bazotte,
Isolde Terezinha Santos Previdelli
Publication year - 2019
Publication title -
revista de matemática e estatística
Language(s) - English
Resource type - Journals
eISSN - 1980-4245
pISSN - 0102-0811
DOI - 10.28951/rbb.v37i1.365
Subject(s) - intervention (counseling) , longitudinal study , medicine , breast milk , glutamine , mixed model , physiology , statistics , demography , food science , zoology , mathematics , biology , psychiatry , biochemistry , amino acid , sociology
Occasionally, the behavior of a response variable monitored over time can be influenced by an intervention performed during the experimental period. With this perspective, this study proposes a simple methodology based on the fitting of two mixed effects models in longitudinal profiles, before and after an intervention, to verify significant differences. The notoriety of this methodology consists of using all repeated observations from the response variable regarding the intervention. This proposed method was motivated by two real datasets. Linear mixed models were fitted in the first dataset, which refers to the CD4 cells count in HIV-positive patients whom, over 30 consecutive days, received a glutamine based food supplement. For the second dataset, nonlinear mixed effects models were fitted for the body mass measurements of preterm newborns whose initial diet was based on breast milk and was subsequently replaced by a commercial food supplement. The proposed methodology was able to identify differences in the growth trend of the CD4 cells count after the observed patients took glutamine based supplementation. Moreover, it provided evidences suggesting the commercial food supplement as an alternative to a breast milk diet in preterm newborns by maintaining the body mass growth trend.