Let’s look at a table of logistic regression coefficients along with the exponentiated coefficients, which some people call odds ratios.

Logistic regression is useful when modeling a binary (i.e. two category) response variable. This newsletter focuses on how to interpret an interaction term between a continuous predictor and a categorical predictor in a logistic regression model.

Apr 26, 2021 · Interactions with Logistic Regression . An interaction occurs if the relation between one predictor, X, and the outcome (response) variable, Y, depends on the value of another independent variable, Z (Fisher, 1926). Z is said to be the moderator of the effect of X on Y, but a X × Z interaction also means that the effect of Z on Y is moderated ...

The regression table: including the coefficients, standard errors, and p-values of the main effects and the interaction term. The interpretation of the coefficient of the interaction term.

•Product terms represent departure from parallel lines. •Translates to departure from proportional odds. •To test proportional odds assumption, test regression coefficients of the product terms.

My own preference, when trying to interpret interactions in logistic regression, is to look at the predicted probabilities for each combination of categorical variables. In your case, this would be just 4 probabilities: Prefer A, control true; Prefer A, control false; Prefer B, …

Adding interaction terms to a regression model can greatly expand understanding of the relationships among the variables in the model and allows more hypotheses to be tested. But interpreting interactions in regression takes understanding of what each coefficient is telling you.

Logistic regression helps us estimate a probability of falling into a certain level of the categorical response given a set of predictors. We can choose from three types of logistic regression, depending on the nature of the categorical response variable: Binary Logistic Regression:

Aug 7, 2019 · In this post, I discuss why this is the case and how it pertains to interactions fitted in logistic regression models.

Table 3 provides the results obtained from Models III and IV, the binary logistic regression with the interaction terms. Model 3 6 provides interaction terms between race and legal...