Dear all,
I am using SPlus 6.1 and running a logistic regression analysis on the
prevalence of fish abnormalities. I have several predictor variables
that are factors and each factor variable has several levels. My data
set is unbalanced.
I do not have a baseline group and for most variables I have many
levels. Therefore, odds ratios are less useful to me than a
standardized prevalence for each level of a factor. I believe
that because my data set is unbalanced the intercept in the output is
not the grand mean and the regression coefficients not directly interpretable
(is this correct?). I would like to be able to use something similar to
"model.tables" to obtain an intercept that I could interpret as the grand mean
(mean prevalence) and regression coefficients and standard errors that can be
used with the intercept to calculate a standardized prevalence (after
back-transforming the logit transformation).
Any advice would be most welcome.
Thank you!
Sincerely,
Mindy Nelson