Comments (3) OK, there are lots of places where it’s written that using RUN statements makes code look cleaner, but that invocation of another PROC statement makes the previous PROC get submitted. So…. It sounds like that RUN statement is a sort of esthetic extra.
But it can bite you
Continue reading 'SAS tip: Why you always should use a RUN statement'»
Description of concordant and discordant in SAS PROC LOGISTIC
Part of the default output from PROC LOGISTIC is a table that has entries including`percent concordant’ and `percent discordant’. To me, this implies the percent that would correctly be assigned, based on the results of the logistic regression. But that is not what it is. It looks at all possible pairs of observations. A pair is concordant if the observation with the larger value of X also has the larger value of Y. A pair is discordant if the observation with the larger value of X has the
smaller value of Y; here, X and Y are the predicted value and the actual value.
Continue reading 'PROC LOGISTIC: Concordant and discordant'»
Description of separation in PROC LOGISTIC
If you picture the data as a 2 x 2 crosstab, then quasi-complete separation occurs when one of the cells is 0. Complete separation occurs when one cell in each row and column is 0.
Continue reading 'PROC LOGISTIC: Complete and quasi-complete separation'»
Description of the problem with effect coding
When you have a categorical independent variable with more than 2 levels, you need to define it with a CLASS statement. In PROC GLM the default coding for this is dummy coding. In PROC LOGISTIC, it’s effect coding. To me, effect coding is quite unnatural.
Continue reading 'PROC LOGISTIC: Reference coding and effect coding'»
The problem of coding 0 and 1 in PROC LOGISTIC
PROC LOGISTIC can be used to run logistic regression on a dichotomous dependent variable. Often, these are coded 0 and 1, with 0 for `no’ or the equivalent, and 1 for `yes’ or the equivalent. In this case, we are usually interested in modeling the probability of a ‘yes’. However, by default, SAS models the probability of a 0 (which would be a `no’).
