When an LSM analysis is run, the solution model provides means adjusted for the effects of the model as well as non-adjusted means for each categorical element in the model. After running a logistic model with multiple predictors or an interaction, is it possible to obtain "adjusted" predictive values with confidence intervals for a different combination of predictors? I would appreciate any guidance or a similar example that deals with this issue.
For example, a logistic regression with two continuous covariates where both Cov1 and Cov2 are significant. How do I obtain values (or visualize) the effect of Cov1 when Cov2 is held at its mean?
Many thanks!
