The prevalence of asthma and declared asthma in Poland on the basis of ECAP survey using correspondence analysis.

Results of epidemiological and public health surveys are often presented in the form of cross-classification tables. It is sometimes difficult to analyze data described in this way and to understand relations between variables. Graphical methods such as correspondence analysis are more convenient and useful. Our paper describes an application of correspondence analysis to epidemiological research. We apply the basic concepts of correspondence analysis like profiles, chi-square distance to medical data concerning prevalence of asthma. We aim at describing the relationship between asthma, region, and age. The data presented in this paper come from Epidemiology of Allergy in Poland (ECAP) survey in years 2006-2008. Correspondence analysis shows that there is a fundamental difference in the structure of age groups for people with symptoms compared to those who have declared asthma (regardless of the level of symptoms of asthma and the level of declaration). The variable which best differentiates declared asthma in all regions is "wheezing and whistling." Correspondence analysis also shows significant differences between locations. Our analyses are performed in the R package "ca".

Selection of medical tests based on linear nonseparability of data sets: a study on evaluation of liver diseases tests.

A new method of solving the problem of medical tests selection is proposed. This method is based on the notion of linear nonseparability of data. A measure of linear nonseparability is computed by minimization of the perceptron criterion function. A multistage strategy of search of the minimum sufficient tests subset is described. This strategy is reliable in the sense that it allows us to find the least (globally) sufficient number of tests. The considerations are illustrated on a liver diseases data example.