Comparison of Classic Discriminant Analysis and Two-state Logistic Regression in Separation of Sardasht City, Iran, Chemical Victims to Mustard Gas Exposed and Non-Exposed Groups

A Review of the late effects of sulfur mustard gas ... [2] Toxicodynamics of sulfur ... [3] Comparison of early and late toxic effects of sulfur mustard ... [4] Lethal intoxication by wargases ... [5] Observation and clinical manifestation of patient ... [6] Studies on DNA repair in early spermatid stages of male mice after in vivo treatment with methyl-, ethyl ... [7] Late manifestations in former mustard gas workers with special ... [8] Concentration of mustard gas [Bis(2-chloroethylin) ... [9] The clinical toxicology of sulfur mustard ... [10] Sardasht-Iran cohort study of chemical warfare ... [11] Fitting logistic model to some quantitative and qualitative variables to discriminate between ... [12] Studying the surrogate validity of respiratory indexes in predicting the respiratory illnesses in ... [13] Quality of life in chemical warfare survivors with ophthalmologic injuries: The first results from Iran chemical ... [14] Comparison of logistic regression and discriminant ... [15] Logistic regression and linear discriminant analyses in evaluating factors associated with asthma prevalence among ... [16] The use of discriminant analysis, logistic regression … [17] Longitudinal discriminant analysis with random effects ... [18] Comparison of artifitial neural network, logistic regression ... [19] Choosing between logistic regression and discriminant … [20] Linear discriminant analysis-a brief ... [21] Comparison of logistic regression and neural network ... [22] Comparison of artificial neural network models with logistic ... [23] Evaluation of serum and sputum level of il-21 in sardasht …Aims The aim of this study was to separate the chemical victims of mustard gas into exposed to and non-exposed groups to sulfur mustard using classical discriminant analysis and twostate logistic regression and selection of the best analysis. Instruments & MethodsThe present study is a historical group that was conducted from 2005 to 2014.By observation method and systematic sampling, 284 people were included in the study including 216 people from Sardasht City as an exposed group and 68 people from Rabat City as a control group who were in all respects compared to the case group.Using classical discriminant analysis and logistic regression methods, 32 quantitative variables were examined and finally these two methods were compared using rock curve analysis.SPSS 21 software was used for analysis.Findings The 8 significant variables that had the highest ability to differentiate the groups (FEV1/FVC ratio, testosterone, cholesterol, phosphorus, conjugated bilirubin, red blood cell count, hemoglobin and hematocrit) were selected and entered into the main models.Using the rock curve, the cutting points of the variables were determined and the sensitivity and specificity values for discriminant analysis were 78% and 77.5%, respectively, and its sub-curved surface was 81.2%.In differentiating the groups, testosterone index was the strongest variable and conjugated bilirubin factor was the weakest variable.In logistic regression model, FEV1/FVC, testosterone and phosphorus ratio variables were significant (p<0.05).The sensitivity and specificity of this model were 80% and 75%, respectively, the rock curvature level was 81.4% and the value of R^2 was 0.308.Conclusion In the separation of chemical victims, the classical discriminant analysis and logistic regression methods have similar results, but discriminant analysis is a more appropriate model due to the presentation of the diagnostic function.