@chemicalab Can you please help me with the code on how we can get the classification table for validation data. Below is my code. proc logistic data=training outmodel=newsModel;       class sex;       model subs=sex age / link=glogit ctable outroc=d;       score data=training out=Score2; run; proc logistic noprint inmodel=newsModel;        score data=validation out=ScoredTest; proc print data=ScoredTest label noobs; ... View more

I have tried that but the result is the same, thank you both for your input, i think i will have to do it via commandline   Kind regards ... View more

"The same way you can use trees. Of course do not expect  the same parsimonious model, that is generated by an algorithm (e.g. UpLift Node in Enterprise Miner ) that creates splits directly maximizing treatment effectiveness" Yes that's exactly what I am after , an upgraded version of the uplift model  from 2 to 4 treatments, Thank you ... View more

Kolmogorov Smirnof chart ... View more

tyang wrote: The reason why I'm not interested in just the regression coefficients is because I want to use the factors (loadings) in a regression equation with an outcome measure that's not part of the response variables. And, I want to be able to use the factors (loadings) in the regression in addition to confounder variables that I want to add into the model. I'm sorry, but apparently my understanding of PLS does not allow me to come to an understanding of what you are asking for. We are simply not communicating here. Again, you seem to me to be explaining tiny portions of the problem you are trying to solve, and I do not see the big picture, nor can I see where you have explained the big picture. What is "an outcome measure that's not part of the response variables"? Why is that a part of this discussion? Please correct me if I'm wrong, but the ods output parameterestimates would give me the equivalent of coefficients for the group of predictor variables that bests predicts the group of response variables? Okay, I am correcting you. The PLS parameter estimates (or regression coefficients) that are computed are for ALL predictor variables. You get one set of regression coefficients for all X variables predicting Y1, another set of regression coeffients for all X variables predicting Y2, and so on for each Y. The loadings indicate the linear combinations of the predictor variables that are "highly predictive" of linear combinations of the response variables ("highly predictive" really means maximized squared covariance between linear combination of X and linear combination of Y, after accounting for the effects of previous dimensions...) ... View more

Hi:   Since part of the URL is the string "sites.stat.psu.edu/~ajw13/stat505", perhaps the ~ajw13 is pointing to this professor whose PSU.EDU web site (with his contact info) also uses "ajw13": stat.psu.edu/people/ajw13 It seemed to me that the animation was done outside of SAS with a different tool, although the individual dendograms might have been generated from PROC TREE.   Not understanding the background source code is a different issue. For example, his first program uses PROC SORT, PROC CLUSTER, PROC TREE, PROC PRINT and PROC GLM all of which you could look up in the documentation.      cynthia http://sites.stat.psu.edu/~ajw13/stat505 ... View more

I have tried the following : proc freq data=OUTPUT.POPULATION (THE SET WITH 95% nonevents and 5% events) noprint;         table TARGET / out=priors(drop=percent rename=(count=_prior_));         run; and i try to score it with the parameters based on the training set: PROC LOGISTIC INMODEL=MODELPARAMETERSTRAINING (the 50-50 sample)  ;      SCORE DATA=OUTPUT.POPULATION PRIOR=PRIORS      OUTROC=ROC     OUT=SCORESPOP PREDICTED=ESTPROB ; RUN; Would that be the correct syntax? I am wondering cause when i compare the estimated probabilities of scoring with or without the priors i see a huge difference in p_1 ... View more

"My goal is to set a measurement or weight that will indicate how well the variable is differentiated in its values and isn't characterized of lets 70% or 80 % of the same value." Are these not variables with platykurtic distributions? Kurtosis - Wikipedia, the free encyclopedia Kurtosis is calculated by many SAS procedures, the most efficient of which would be PROC HPDMDB. http://support.sas.com/documentation/cdl/en/prochp/66704/PDF/default/prochp.pdf "I have noticed many bugs and wrongs in Eminer computations" - like what? I am not only a developer for Enterprise Miner - I am also a certified Predictive Modeler for Enterprise Miner and I use it nearly everyday for very complex tasks. While I occasionally see things that I think are bugs, it's nearly always something I just don't understand. Enterprise Miner is tested for functionality and numerical validity year-round by a team of professional statisticians, data miners, programmers and testers all over the world. It is extremely unlikely that such a team could miss "many bugs and wrongs in Eminer computations". However, if you truly think there are problems, these need to be reported to SAS technical support immediately. ... View more

Thank you for the reply, unfortunately i am running on SAS base ... View more

Unfortunately i dont have EM so i guess i will have to go with Proc Princ or Varclus, thank you for the reply ... View more