This is something Technical Support could address. You can send email from here https://support.sas.com/en/technical-support.html#m-create-email ... View more

You could disable ODS Graphics and use an AXIS statement, such as   ods graphics off; axis1 order=(0 to 50 by 10) value=('0%' '10%' '20%' '30%' '40%' '50%')        label=("Pts Counseled") minor=none; proc shewhart data=tmp2;   pchart yes_answer2*month / subgroupn = n_per_group2 ODSTITLE="P-chart of Pts Counseling"        outtable = tmp2table        vaxis=axis1        nohlabel nolegend YSCALE=PERCENT ; run; ods graphics on; ... View more

The central line in the s chart varies when the subgroup sizes vary, so it's not labeled. See Constructing Charts for Standard Deviations.     ... View more

You can use the NOCHART2 option in the XSCHART or the XRCHART statement to suppress the secondary chart.   proc shewhart data=MIS; xSchart LOS*AdmitYYQ / Markers     outtable=outtable   nochart2; run; ... View more

If you were computing the average percent, you would sum the percentages and divide by N to get (.1+.2+.1+.2+.4)/5=0.2 . But here we are averaging proportions and the sample size should technically not be ignored. > I don't want to use subgroupN, because that would exclude lot 5 from contributing to the calculation of the control limits. The SUBGROUPN option specifies the n_i  values to use in computing pbar.  This allows for the case you describe, where you want all proportions to have equal weight, in that sense. Lot 5 is not excluded by SUBBGOUPN=20. Its contribution in the numerator becomes 20*.4 instead of 60*.4, and it gives you the pbar you want. This is how PROC SHEWHART lets you specify the relative contribution of each proportion.  proc shewhart data=have ;   pchart pfailed*lot/subgroupn=20 dataunit=proportion; run ;         ... View more

I don't know if I would consider the default pbar as a weighted average in PROC SHEWHART.  data have ;   input lot pfailed ntested;   nfailed=pfailed*ntested; cards ; 1 .1 20 2 .2 20 3 .1 20 4 .2 20 5 .4 60 ; proc print;   sum pfailed ntested nfailed; run; pbar = 36/140=0.257, so just the average proportion failed. If you want the control limits computed using the same subgroup sample size, you could do proc shewhart data=have ;   pchart pfailed*lot/subgroupn=20 dataunit=proportion; run ; Now the control limits are constant because the subgroup sample sizes are constant. If you ignore the subgroup sample sizes, the varying control limits are not correct.     ... View more

This is the SGPLOT result so far: And the LIFETEST plot already has the medians and censored summary. I'm thinking the LIFETEST KM plot is closer to being done than the SGPLOT KM plot, yes? If you can tell me what you want excluded from the LIFETEST plot, and exactly what you want added and where, I might be able to provide code.  ... View more

Depending on what you want, you might be able to do the customizations directly in PROC LIFETEST, using the macros.   But you can save the Quartiles and the CensoredSummary ODS output data sets in order to capture the data in the added table. I used the %SurvivalSummaryTable to add the Number of Patients, etc. in the example below:   ods path(prepend) work.templat(update); data _null_;   %let url = //support.sas.com/documentation/onlinedoc/stat/ex_code/151;   infile "http:&url/templft.html" device=url;   file 'macros.tmp';   retain pre 0;   input;   _infile_ = tranwrd(_infile_, '&amp;', '&');   _infile_ = tranwrd(_infile_, '&lt;' , '<');   if index(_infile_, '</pre>') then pre = 0;   if pre then put _infile_;   if index(_infile_, '<pre>') then pre = 1; run; %inc 'macros.tmp' / nosource; %ProvideSurvivalMacros %SurvivalSummaryTable %CompileSurvivalTemplates data bmt;   set sashelp.bmt;   xval = 250;   yval = 0.2; run; ods select SurvivalPlot; proc lifetest data=bmt plots=(survival(cb=hw atrisk=0 to 2500 by 500));   time T*status(0);   strata group /test=logrank adjust=sidak;   ods output Quartiles=Quartiles CensoredSummary=Summary; run;   proc print data=Quartiles;   where percent=50; run; proc print data=Summary; run;   ... View more

You would use SURVEYREG with the default VARMETHOD=TAYLOR. ... View more

PROC SURVEYIMPUTE generates imputation-adjusted replicate weights that you then use in another survey procedure. This is different than a multiply imputed data set, so you do not need to use PROC MIANALYZE. Instead, read the imputed data into PROC SURVEYREG and specify the replication method for variance estimation using the VARMETHOD= option. The imputation variance will be accounted for. The Getting Started example in PROC SURVEYIMPUTE explains it well. ... View more

Sorry about the typo!    Try adding the statement   ODS _ALL_ CLOSE;   at the beginning of your program. If you are specifying an ODS destination, with an ODS PDF or ODS RTF statement, for example, you might need to modify the syntax there as well. I'm not an expert in this area, so if this doesn't work, include your full code or log and someone else might weigh in, or you could contact Technical Support. ... View more

Here's one approach: proc univariate data=sashelp.class noprint;   class sex;   histogram height/ nobars normal(noprint);   ods ouput histogram=hist; run; data hist;   set hist;   lower=0; run; proc sgplot data=hist;   series x=CurveX y=CurveY/group=Class1;   band x=CurveX lower=lower upper=CurveY/group=Class1 transparency=.5; run;     ... View more