True or false: Unlike in linear regression, it is possible to have more than one dependent variable in a logistic regression model.

• A. True
• B. Sometimes True
• C. False
• D. Cannot Be Determined

Answer: (C)

The main idea is that logistic regression is built to model a single outcome variable, typically binary. In its standard form, you predict the probability of one event happening given the predictors, using a logit link to map predictors to that probability. If the outcome has more than two categories, you use multinomial logistic regression, which still treats it as one dependent variable with multiple categories, not multiple dependent variables. If there are several different outcomes to model, you don’t typically put them all into one logistic regression equation; you’d either run separate logistic regressions for each outcome or use a more advanced multivariate approach. So, the statement is false: you don’t have more than one dependent variable in a single standard logistic regression model.