In many cases research focuses on models where the dependent variable is categorical. Instead we would carry out a logistic regression analysis. Hence, logistic regression may be thought of as an approach that is similar to that of multiple linear regressions, but takes into account the fact that the dependent variable is categorical. Binary responses are commonly studied in many fields. Examples include the presence or absence of a particular disease, death during surgery, or a consumer purchasing a product. However, in many situations, there are multiple descriptors, or one or more of the descriptors are continuous. Without a statistical model, studying patterns such as the relationship between age and occurrence of a disease, for example, would require the creation of arbitrary age groups to allow estimation of disease prevalence as a function of age. . In biomedical research it is common to observe multivariate time series data where the outcomes are binary. the purpose of analysis include assessing the association among variable at one time, identifying lead lag relationships among variables, and regressing, one outcome on others as well as on fixed covariates. In this paper the in cadence of tuberculosis using binary Logistic regression has been studied.
