Estimating odds ratiosEstimate the odds ratios using a logistic model.

Ensure you have followed the steps in Fitting a simple logistic regression or Fitting an advanced logistic model.

Activate the analysis report worksheet.
On the Analyse-it ribbon tab, in the Fit Model group, click Odds Ratios.
The analysis task pane Odds Ratios panel opens.

In the Odds Ratios grid, in the Comparison column.: For a continuous variable, type the change in units of the predictor for the odd ratio, the default is for 1 unit change in the predictor, but for some predictors the odds ratio for a 10 or 100 unit change in the predictor maybe more interpretable. For a categorical variable, select the type of comparison:

Option	Description
All pairs	Compare all pairs of categories against each other. For example, with 3 categories the comparisons, are 1v2,1v3,2v1,2v3,3v1,3v2.
All distinct pairs	Compare all unique pairs of categories against each other. For example, with 3 categories the comparisons as 2v1,3v1,3v2).
Against reference	Compare all categories against the reference category (the first category in the categorical variable). For example, with 3 categories the comparisons are 3v1, 2v1.

If the model has interaction terms, in the At column for each continuous variable involved in an interaction, type the levels of interest as a comma (or your list delimiter) separated list. For example, if Age is a variable involved in an interaction with Gender, you may use 16, 25, 30, 40, and 60 as the levels of interest at which the Gender Female/Male odds ratios will be computed. For a continuous variable involved in an interaction with a categorical variable, the unit change for each level of the categorical variable will be computed. For example, if the Age unit is 10 years and Age is involved in an interaction with Gender, the odds ratio for a change of 10 years will be computed for Females and Males.
In the Confidence interval edit box, type the confidence level.
Click Recalculate.