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Table and Symbols in a Logistic Regression

Source B SE B Wald χ2 p OR 95% CI OR Variable 1 1.46 0.12 7.55 .006 4.31 [3.26, 5.35] Variable 2 -0.43 0.15 6.31 .012 0.65 [0.18, 0.83] Note. OR = odds ratio. CI = confidence interval The table for a typical logistic regression is shown above.  There are six sets of symbols used

Binary Logistic Regression

Logistic regression is an extension of simple linear regression. Where the dependent variable is dichotomous or binary in nature, we cannot use simple linear regression. Logistic regression is the statistical technique used to predict the relationship between predictors (our independent variables) and a predicted variable (the dependent variable) where the dependent variable is binary (e.g.,

Logistic Regression

Logistic regression is an extension of multiple linear regressions, where the dependent variable is binary in nature. It predicts the discreet outcome, such as group membership, from a set of variables that may be continuous, discrete, dichotomous, or of any other type. Logistic regression is an extension of discriminant analysis. Discriminant analyses also predict the