Seleção de covariáveis para ajuste de regressão logística na análise de abundância de invertebrados edáficos em diferentes agroecossistemas / Covariates selection for logistic regression adjustment in analysis of edaphic invertebrates abundance in different agroecosystems

AUTOR(ES)

Luciane da Silva Oliveira

FONTE

IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia

DATA DE PUBLICAÇÃO

25/02/2011

RESUMO

Logistic regression is the analysis usual statistical method used to verify the relationship between a dichotomous variable response and the interest explanatory variables. This work aimed to carry out a study about the factors influencing the invertebrates abundance on the soil under different management forms, using the logistic regression. This objective is that these invertebrates are considered excellent indicators of the use type and soil quality, working in several fundamental processes for maintaining the soil fertility and quality in agroecosystems and natural ecosystems, according to Brown et al. (1998), Hendrix et al. (2006), and Souza (2010). For covariates selection, the Collett (1994) proposal was used and the involved parameters estimators in each model, their interpretations, statistical properties, and some criteria for judging the suitability of the selected models were presented. The methodology presented by this work was applied to two real datasets (dry and rainy season). In the final adjusted model for the analyzed dataset in the dry season, it was verified that the covariates System Type, Calcium in litter, Soil organic matter, Potassium in litter, and the interaction between Calcium and Potassium in litter were important to explain the presence of more than nine individuals on the soil. In the final adjusted model for the analyzed dataset in the rainy season, the significant covariates to explain the presence of one hundred and one individuals on average on the soil were Magnesium in litter, Total organic carbon in the litter, Litter organic matter, and Ambient temperature. For two mentioned models, there were a good discriminatory performance and excellent areas under the ROC (Receiver Operating Characteristic) curve, thus confirming the validity of using logistic regression techniques for the models construction to describe the analyzed data.

ASSUNTO(S)

invertebrados edáficos seleção de covariáveis regressão logística ciencias agrarias logistic regression edaphic invertebrates covariates selection

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