Theoretical Modeling of AIDS Infections and Disease Persistence

Abstract

We argue in this paper that it is more feasible to use binary variables and logistic regression analyses in the assessments of AIDS incidents o or other similar researches in social science. Thus, even in measuring disease persistence we can reach solid and comprehensive results. Statistical methods consider the analysis of relationships between measurements made on groups of subjects or objects. The measurements might be the heights or weights and the ages of boys and girls, or the yield of plants under various growing conditions. Additionally, we use the terms response, outcome or dependent variable for measurements that are free to vary in response to other variables called explanatory variables or predictor variables or independent variables although this last term can sometimes be misleading. Responses are regarded as random variables. Explanatory variables are usually treated as though they are non- random measurements or observations. They can be fixed by the experimental design, responses and explanatory variables.