Hello,   Is this an Enterprise Guide Process Flow?? If yes, I will move this topic to a more appropriate board: Home > Programming > Enterprise Guide   If it's matter of pure programming in SAS Studio or Display Manager, I can easily help you out, ... but this is about looping through an EG-process flow multiple times I am afraid. Meanwhile I have forgotten how to do that.   BR, Koen ... View more

https://support.sas.com/sassamples/graphgallery/PROC_SGPLOT.html Sample 42542: Plot means with standard error bars from calculated data with PROC SGPLOT https://support.sas.com/kb/42/542.html Sample 35053: Mean percent change in allergy relief https://support.sas.com/kb/35/053.html Sample 35169: Stock chart https://support.sas.com/kb/35/169.html Koen ... View more

This is about template modification: A SAS programming technique to modify ODS templates By Rick Wicklin on The DO Loop October 30, 2017 https://blogs.sas.com/content/iml/2017/10/30/programming-modify-ods-templates.html SAS/STAT 15.3 User's Guide ODS Graphics Template Modification https://go.documentation.sas.com/doc/en/pgmsascdc/9.4_3.5/statug/statug_templt_toc.htm https://blogs.sas.com/content/?s=template+modification Koen ... View more

Hello,   Not sure if UNEQUALSLOPES can be done in a multinomial logit model that is fit with PROC GLIMMIX (because there are mixed effects).   I cannot see that covered in: Usage Note 22871: Types of logistic (or logit) models that can be fit using SAS® (Date Modified: 2018-09-18 11:31:00) https://support.sas.com/kb/22/871.html   6 times the string "unequal" is there on that page, but not when GLIMMIX is talked about.   Last update of above usage note was done in September 2018, so maybe @StatDave has more info??   BR, Koen ... View more

Hello,   Here are some example LSMEANS statements. I think you can find inspiration in the 3 last ones (with at and slice).   PROC MIXED : lsmeans adhesive / diff cl alpha=0.10; PROC MIXED : lsmeans pretrt stain / diff adjust=tukey adjdfe=row; PROC MIXED : lsmeans drug / diff=control('p') adjust=dunnett adjdfe=row; PROC MIXED : lsmeans Trt / e diff; PROC MIXED : lsmeans gender*age / slice=gender slice=age; PROC GLIMMIX : lsmeans trt / oddsratio ilink diff; PROC MIXED : lsmeans temp / at thick=1850 diff; PROC MIXED : lsmeans Trt / at flush0=50 diff; PROC MIXED : lsmeans drug*hour / slice=hour diff adjust=tukey adjdfe=row;   Koen ... View more

Hello,   Never use ESTIMATE or CONTRAST statements when you can also achieve the wished for analyses by using LSMEANS, SLICE, or LSMESTIMATE statements.   If ESTIMATE or CONTRAST statements cannot be avoided, take care because they are sometimes difficult to specify (program) correctly. Below are some blogs and usage notes on correct usage!   The magical ESTIMATE (and CONTRAST) statements By Chris Daman on SAS Learning Post April 23, 2012 https://blogs.sas.com/content/sastraining/2012/04/23/the-magical-estimate-and-contrast-statements/ "Easy button" for ESTIMATE statements By Chris Daman on SAS Learning Post April 25, 2012 https://blogs.sas.com/content/sastraining/2012/04/25/easy-button-for-estimate-statements/ ESTIMATE Statements - the final installment By Chris Daman on SAS Learning Post May 2, 2012 https://blogs.sas.com/content/sastraining/2012/05/02/estimate-statements-the-final-installment/ How to write CONTRAST and ESTIMATE statements in SAS regression procedures? By Rick Wicklin on The DO Loop June 6, 2016 https://blogs.sas.com/content/iml/2016/06/06/write-contrast-estimate-statements-sas-regression-procedures.html Usage Note 24447: Examples of writing CONTRAST and ESTIMATE statements https://support.sas.com/kb/24/447.html Usage Note 67024: Using the ESTIMATE or CONTRAST statement or Margins macro to assess continuous variable effects in interactions and splines 67024 - Using the ESTIMATE or CONTRAST statement or Margins macro to assess continuous variable effects in interactions and splines (sas.com) When a model contains interactions, it is often of interest to assess the effect of one of the interacting variables. When the variable of interest is categorical, and therefore is specified in the CLASS statement, this is most easily done using the LSMEANS, SLICE, or LSMESTIMATE statement. But when the variable of interest is continuous, these statements cannot be used. Two procedures, LOGISTIC and PHREG, provide statements that can estimate the effect of increasing a continuous predictor by a specified number of units. However, when the modeled response is not binomial or a time to event, these procedures are not appropriate. Nevertheless, the HAZARDRATIO statement in PROC PHREG can still be used to provide contrast coefficients that can be used in CONTRAST or ESTIMATE statements to test or estimate the effect of a continuous predictor. This can be done for a continuous predictor involved in one or more interactions and even in constructed effects such as splines. In the case of generalized linear models that don’t use the identity link, it is important to note that the estimated effect using these coefficients is not a difference in response means. For these models, an alternative and generally easier solution is provided by the Margins macro, which can estimate the required difference in means. Both of these approaches are discussed and illustrated in this note.   Koen ... View more

Hello @jhmoon ,   @Rick_SAS is correct. I was wrong in my 1st reply. I had read the GLMSELECT doc to quickly. https://go.documentation.sas.com/doc/en/pgmsascdc/9.4_3.5/statug/statug_glmselect_syntax03.htm#statug.glmselect.glsclassparam   This is what it says: =========== PARAM=keyword specifies the parameterization method for the classification variable or variables. Design matrix columns are created from CLASS variables according to the following coding schemes. If the PARAM= option is not specified with any individual CLASS variable, by default, PARAM=GLM. Otherwise, the default is PARAM=EFFECT. If PARAM=ORTHPOLY or PARAM=POLY, and the CLASS levels are numeric, then the ORDER= option in the CLASS statement is ignored, and the internal, unformatted values are used. See the section CLASS Variable Parameterization and the SPLIT Option for further details. =========== Koen   ... View more

You need a "Random Coefficient Model" with random intercepts and random slopes for each "class"?   See this paper: Paper SAS026-2014 Analyzing Multilevel Models with the GLIMMIX Procedure Min Zhu, SAS Institute Inc. https://support.sas.com/resources/papers/proceedings14/SAS026-2014.pdf   This PROC GLIMMIX is on page 11. proc glimmix data=mctrial; class patient center treat; model dbp = dbp1 treat visit / solution; random intercept visit / subject = center type=chol; random intercept / subject = patient(center) ; covtest 'Diagonal G' DIAGG; estimate 'Carvedil vs. Atenolol' treat 1 -1 0; estimate 'Carvedil vs. Nifedipi' treat 0 1 -1; run; Koen ... View more

Hello,   I have moved this topic thread to another board that is more appropriate for this query of yours. Home > Analytics > SAS/IML "SAS/IML software and matrix computations"-board   You say : "... but when I include this variable, the code does not run." Does it generate a WARNING or an ERROR in the LOG??   Also, when copying and pasting SAS-code, click the little "running man" squared icon in the header, ... you then get a pop-up window in which you can paste your code. That way, formatting and structure are preserved and font is mono-spaced.   Koen ... View more

Hello,   There's a different parameterization method for the classification variables in PROC GLM and PROC GLMSELECT PROC GLM --> PARAM=GLM (no choice, param= does not even exist as an option)  PROC GLMSELECT --> the default is PARAM=EFFECT. (Effect coding = deviation-from-the-mean coding) You can specify PARAM=GLM in PROC GLMSELECT CLASS statement (after forward slash). PARAM=GLM specifies less-than-full-rank, reference-cell coding; this option can be used only as a global option (i.e. for all class effects). You need to specify PARAM=GLM in PROC GLMSELECT to mimic the design matrix from PROC GLM.   Koen ... View more

Hello,   I moved this topic (question) to a more appropriate board. Home > Solutions > Decisioning.   Koen   ... View more

Hello,   Maybe there's a solution within PROC PHREG (I don't know PROC PHREG well enough). Otherwise I think you can use PROC FREQ for trend test.   The below info is taken from  Usage Note 30333: FASTats: Frequently Asked-For Statistics https://support.sas.com/kb/30/333.html Cochran-Armitage trend test See Trend test for ordered alternatives Jonckheere-Terpstra test See Trend test for ordered alternatives. Trend test for ordered alternatives For binary responses: Cochran-Armitage test in Base SAS PROC FREQ (TREND option in TABLES statement); SAS/STAT PROC MULTTEST (CA option in TEST statement); score test in SAS/STAT PROC LOGISTIC (equivalent to the Cochran-Armitage test). For binary or multilevel responses: Jonckheere-Terpstra test in Base SAS PROC FREQ (JT option in the TABLES statement). For continuous responses: Use Base SAS PROC CORR with KENDALL option. The p-value for the Kendall statistic is equivalent to the two-tailed p-value for the Jonckheere statistic. The one-tailed p-value is half this p-value. If the number of distinct response values is small, Base SAS PROC FREQ with the JT option can also be used. In small sample situations, an exact test is available (use the EXACT JT; statement). Koen ... View more

Hello,   "Independent predictors"? All candidate predictors are independent variables. I have never heard about "independent predictors", that's a tautology.   Concerning your question: mref is a class variable to which glm-coding is applied. class mref(ref='0')/param=glm; You have to learn about the coding schemes for class-effects : glm , effect coding (=deviation-from-the-mean coding), reference cell coding , ...   See here: SAS/STAT 15.3 User's Guide The LOGISTIC Procedure Example 79.2 Logistic Modeling with Categorical Predictors https://go.documentation.sas.com/doc/en/pgmsascdc/9.4_3.5/statug/statug_logistic_examples02.htm UCLA CODING SYSTEMS FOR CATEGORICAL VARIABLES IN REGRESSION ANALYSIS https://stats.oarc.ucla.edu/spss/faq/coding-systems-for-categorical-variables-in-regression-analysis/ (that's for SPSS, but that doesn't matter much because largely the same in all stat software) When interpreting coefficients from a class effect, you must know how it was coded (mandatory for proper interpretation)!   If you only have 0 and 1 values for your mref and mref is a variable having the numeric data type, then you might consider to include it as a "continuous" covariate in your linear predictor. Just get rid of the class statement.   Cheers, Koen ... View more

Hello,   Maybe you need to do this:   DATA source role : In the Data Source Wizard — Data Source Attributes window, change the data source role from Raw to Transaction.   Koen ... View more