Linear mixed model for weight analysis in mice infected by Trypanosoma cruzi

The use of linear mixed models for nested structure longitudinal data is called hierarchical linear modeling. This modeling takes into account the dependence of existing data within each level and between hierarchical levels. The process of modeling, estimating and analyzing diagnoses was illustrate...

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Bibliographic Details
Published in:	Acta scientiarum. Health sciences Vol. 42; no. 1; p. e49916
Main Authors:	Pereira, Roney Peterson, Guedes, Terezinha Aparecida, Ferreira, Érika Cristina, Araújo, Silvana Marques de, Ricardini, Larissa Aparecida, Ciupa, Larissa
Format:	Journal Article
Language:	English
Published:	Maringa Editora da Universidade Estadual de Maringá - EDUEM 01-01-2020 Universidade Estadual de Maringá
Subjects:	Chagas disease epidemiology and biostatistics; statistical models; chagas disease Evolution Health sciences Immunology Infections Medical research Parameter estimation Protozoa Quantitative genetics Variables
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Summary:	The use of linear mixed models for nested structure longitudinal data is called hierarchical linear modeling. This modeling takes into account the dependence of existing data within each level and between hierarchical levels. The process of modeling, estimating and analyzing diagnoses was illustrated through data on the weights of mice experimentally infected by Trypanosoma cruzi, divided into different treatment groups, with the purpose of verifying the evolution of their body weight as a result of using different types of biotherapeutics produced from Gallus gallus domesticus (chicken) serum to treat Trypanosoma cruzi. Through the model selection criteria AIC and BIC and the likelihood ratio test, a model was chosen to describe the data correctly. Model diagnoses were then performed by means of residual analysis for both levels and an analysis of influential observations to verify if any observations were signaled as influencing the fixed effects, the components of variance and the adjusted values. After the analysis, it was possible to notice that the observations that were signaled as influential had little impact on the Model chosen initially, so it was maintained, with no differences being evidenced between the treatments with the biotherapeutics tested; only the Time variable and the Random intercept were necessary to describe the weight of the mice.
ISSN:	1679-9291 1807-8648
DOI:	10.4025/actascihealthsci.v42i1.49916