# Benefits to fitting a separate logistic regression model for each independent variable?

Is there any benefit to doing a for loop so that a logistic regression model is fit separately for each independent variable (i.e. 100 models all using the same dependent variable)? As opposed to fitting one model with all 100 independent variables and the dependent variable.

• Why do you think there would be an advantage? The disadvantages are numerous: Increased omitted variable bias, no way to incorporate interactions, no way to prevent confounding from any of the 99 remaining explanatory variables. Oct 30 '19 at 13:23
• @FransRodenburg I don’t know that there would be an advantage. That’s why I was asking the question. Oct 30 '19 at 13:48
• Depending on how much data you have, 100 variables may be more than you have enough information for (cf, Logistic regression with small number of cases). Oct 31 '19 at 19:02