Repository logo

Matemática e Estatística | Comunicações em congressos, conferências e seminários / Communications in congresses, conferences

Permanent URI for this collection

http://hdl.handle.net/10400.2/1638

Browse

Browsing Matemática e Estatística | Comunicações em congressos, conferências e seminários / Communications in congresses, conferences by Sustainable Development Goals (SDG) "03:Saúde de Qualidade"

Now showing 1 - 2 of 2
  • Comparison of discriminant analysis methods: Application to occupational exposure to particulate matter
    Publication . Ramos, Maria do Rosário; Carolino, E.; Viegas, Carla; Viegas, Sandra
    Health effects associated with occupational exposure to particulate matter have been studied by several authors. In this study were selected six industries of five different areas: Cork company 1, Cork company 2, poultry, slaughterhouse for cattle, riding arena and production of animal feed. The measurements tool was a portable device for direct reading. This tool provides information on the particle number concentration for six different diameters, namely 0.3 μm, 0.5 μm, 1 μm, 2.5 μm, 5 μm and 10 μm. The focus on these features is because they might be more closely related with adverse health effects. The aim is to identify the particles that better discriminate the industries, with the ultimate goal of classifying industries regarding potential negative effects on workers' health. Several methods of discriminant analysis were applied to data of occupational exposure to particulate matter and compared with respect to classification accuracy. The selected methods were linear discriminant analyses (LDA); linear quadratic discriminant analysis (QDA), robust linear discriminant analysis with selected estimators (MLE (Maximum Likelihood Estimators), MVE (Minimum Volume Elipsoid), "t", MCD (Minimum Covariance Determinant), MCD-A, MCD-B), multinomial logistic regression and artificial neural networks (ANN). The predictive accuracy of the methods was accessed through a simulation study. ANN yielded the highest rate of classification accuracy in the data set under study. Results indicate that the particle number concentration of diameter size 0.5 μm is the parameter that better discriminates industries.
    2016Conference object Restricted access Show more
  • Two-way MANCOVA: an application to public health
    Publication . Ramos, Maria do Rosário; Carolino, E.; Oliveira, T.; Bicho, M.
    The aim of this work is to use the MANCOVA model to study the influence of the phenotype of an enzyme – Acid phosphatase – and a genetic factor – Haptoglobin genotype – on two dependent variables - Activity of Acid Phosphatase (ACP1) and the Body Mass Index (BMI). Therefore it's used a general linear model, namely a multivariate analysis of covariance (Two-way MANCOVA). The covariate is the age of the subject. This covariate works as control variable for the independent factors, serving to reduce the error term in the model. The main results showed that only the ACP1 phenotype has a significant effect on the activity of ACP1 and the covariate has a significant effect in both dependent variables. The univariate analysis showed that ACP1 phenotype accounts for about 12.5% of the variability in the activity of ACP1. In respect to this covariate it can be seen that accounts for about 4.6% of the variability in the activity of ACP1 and 37.3% in the BMI.
    2012Conference object Restricted access Show more