Creating segmented models in SAS is quite easy, with a by group processing . It is less easy in other softwares , but that is understandable given that
the first generic rule of segmentation is
1) each segment has statistically similar characteristics .
2) different segments have statistically different characteristics .
This means that just using Proc freq to
check response rate versus
independent variable is not a good way
to check the level of difference.
Proc univariate with plot option and
a by group processing
is actually a better way to test out
because it is a combination of means ,
median analysis
(measures of central value) but also
box plot ,normal distributions and standard deviations
(measures of dispersion).
Proc freq with cross tab is incredibly powerful to decide whether to create a model in the first place. But fine tuning of decisions on segments is better done with proc univariate. The SAS equivalent for clustering of course remains Proc Fastclus and family which will be dealt in a separate post.
(Note :lovely image that explains the above from Dr Ariel Shamir’s home page (he is a research expert on Visual Succinct Representation of Information ————-from Israel, land of the brave and intelligent).
A Picture is truly worth a thousand words (or posts !).)
DECISION STATS 