Logistic Regression Essay ⋆ Political Science Essay Examples ⋆ EssayEmpire

Logistic regression is a multivariate statistical technique used to study the relationship between a set of exogenous or independent variables on a binary endogenous or dependent variable. Sometimes called a logit regression or a logit model, a logistic regression is a special case of a discrete regression and is closely related to the probit model. The dependent variable in a logistic regression is usually an indicator variable that takes on one of two values. Logistic regressions are used to study the factors that predict candidate choice (Democrat versus Republican) in two-candidate elections, outcomes (alive versus dead) of medical trials, the causes of employment (employed versus unemployed), and so forth. The logistic regression is based on the logistic curve, a mathematical function that maps the real line into the unit interval. There are many extensions of the basic logistic regression, and these extensions are found in modern statistical software packages. Some of the more common extensions include the multinomial logistical regression, in which a categorical dependent variable of interest takes on multiple categories as opposed to only two; the ordered logistic regression, in which a categorical dependent variable of interest takes on multiple categories that have a natural order ing; and the conditional logistical regression, a model used to study individual choice in which features of the discrete options under consideration are modeled jointly with features of the individuals who are making choices.

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