Hi experts, I generated an output using SGpanel, however for my y-axis variable (Enrollment_Year 2017, 2018, 2019, 2020, 2021, 2022), the graph output is giving me labeling only for even years and skipping out odd year labeling on the graph.    Thank you for your help in advance! proc means data=bar1 noprint nway; class measure Enrollment_year ; var score ; where score >.; output out=bytype (drop=_type_ _freq_) n(score)=n mean(score )=mean uclm(score)=uclm lclm(score )=lclm; run; * also make an overall graph; proc means data=bar1 noprint nway; class Enrollment_year ; var score ; where score >.; output out=bytypeall (drop=_type_ _freq_) n(score)=n mean(score )=mean uclm(score)=uclm lclm(score )=lclm; run; data bytypeall; set bytypeall; measure="OVERALL"; run; data bytype2; set bytype bytypeall; Activity=measure; * just renaming; meanround=round(mean,.1); format meanround 4.1; group=measure ||' '|| Enrollment_year || ' '||(put(n,$3.))||' '||put(meanround,f4.1) ; typen= Enrollment_year || ' '||(put(n,$3.))||' '||put(meanround,f4.1) ; labelatzero=.01; labelatzero2='N = '||(put(n,$3.)); *if activity='OVERALL' then labelatzero2=' '; run; title 'Dont use this plot because there are not enough practices in act 1 to 10 in early years'; * the problem with sgpanel is the number of graphs to look at is uneven and height cant be specified - ah - can change height though!; ods graphics on / border=off height=10in width=8in noscale outputfmt=png ; proc sgpanel data=bytype2 ; panelby Activity/ layout=panel border /*noheaderborder*/ columns=2 rows=8 skipemptycells /*onepanel*/ headerbackcolor=lightgrey headerattrs=(family=arial size=9 weight=bold color=black); highlow y=Enrollment_year high=uclm low=lclm/ type=bar barwidth=.5 nooutline fillattrs=(color=cx42A5F5) transparency=.3 name='bar' legendlabel='95% Confidence Interval'; scatter y=Enrollment_year x=mean/Markerattrs=( Symbol=CIRCLEFILLED color=black Size=12) NAME="dot" legendlabel='Mean'; colaxis label='Score' min=0 max=4 values=(0 1 2 3 4) labelattrs=(family=arial size=10 weight=bold color=black); rowaxis label='Enrollment Year' labelattrs=(family=arial size=8 weight=bold color=black) REVERSE ; text y=Enrollment_year x=labelatzero text= labelatzero2; keylegend 'dot' 'bar'; run;   ... View more

Hi experts, I have a huge string variable Shared_interests (only 19 out of 150 responded to this question. But the response is a huge text string "Other. Shared care management and care coordination system for medical needs Shared infrastructure for social needs services. Shared management structure. Shared personnel responsibilities. Shared physical infrastructure. Shared revenues and expenses. Shared technical infrastructure including EMR and other IT. Sharing of best practices." I have to create new variables from this and I tried a few methods (by using like, contains, =:, %) but unsuccessful. I would appreciate your help greatly.     Data a; Set a; if Shared_services =: "management structure" then managementn=1; else managementn=0; if Shared_services =: "physical infrastructure" then physical_infrastructuren=1; else physical_infrastructuren=0; if Shared_services =: "personnel responsibilities" then personnel_responsibilitiesn=1; else personnel_responsibilitiesn=0; if Shared_services =: "revenues and expenses" then revenues_and_expensesn=1; else revenues_and_expensesn=0; if Shared_services =: "technical infrastructure" then technical_infrastructuren=1; else technical_infrastructuren=0; if Shared_services =: "care management" then care_managementn=1; else care_managementn=0; if Shared_services =: "social needs services" then social_needs_servicesn=1; else social_needs_servicesn=0; if Shared_services =: "best practices" then best_practicesn=1; else best_practicesn=0; if Shared_services =: "Other" then shared_othern=1; else shared_othern=0; run;     Thank you   ... View more

Dear experts, I need to find the intraclass correlation coefficient (ICC) between two different variable (X vs Y) in a data set. I have a list of 10 subjects and measurements were taken at time1 (variable X) and at time2 (variable Y). Similarly I have to compare X1 vs Y1, X2 vs Y2,....X34 vs Y34. I would really appreciate your help with this. I do not want to do a data step for each of these comparisons 34 times. Is there a better way to handle this?   Data variables/ columns in the data set:   ID   X  Y X1 Y1 X2 Y2 X3 Y3....X34 Y34 1 2 3 4 5 6 7 8 9 10   Thanks a bunch in advance! SM ... View more

Dear SAS experts, I have a summary data set with means and standard deviations (SD) for a continuous variable, force (Fx) measured on about 5000 subjects. This force, Fx is measured at 10 different time points (baseline, 8 hours, 16 hrs, 24 hrs, 48 hrs, 3days, 4 days, 5 days, 6 days, 7 days and 14 days). I would like to know what is the best statistical analysis for checking if there is any significant difference between the mean values? Should I use linear regression or something like a Cochran Armitage trend test? Any help with this would be much appreciated.   Data have: Time Fx_Mean Fx_SD 8 Hours 2.706 1.725 16 Hours 1.868 1.637 24 Hours 2.103 2.064 48 Hours 2.482 2.186 Day 3 2.328 2.179 Day 4 2.490 2.076 Day 5 2.308 2.000 Day 6 2.217 2.005 Day 7 2.644 2.019 Day 14 2.546 1.596   Thank you so much, SM ... View more

Dear SAS experts, I have a set of cancer cases and age and sex matched (1:5) controls in the dataset. I am looking back in time to see if the cancer cases have a significantly increased % of diabetes leading up to cancer compared to the controls. For cancer cases, I used cancer date as the index date and for controls, I have selected an arbitrary date when they came for follow-up in the system. For both cancer cases and controls, I looked back in time to see if they had a diabetes diagnosis. Among cancer cases and controls who had a diabetes diagnosis, I calculated the time from index date to diabetes date. When I plot the results, I definitely see increased % of diabetes in cancer cases compared to controls.                                                How do I test the significance of this increased % in cancers compared to controls? I need to adjust for race and other cofactors as well. I want to show that each year prior to index date, the % of diabetes in cancer cases are significantly higher compared to controls and fit a overall model and also maybe a graph (like reverse KM curve or cumulative incidence curve?). I have attached an excel sheet with the % of diabetes identified in cancer cases and controls.    Any help with this is greatly appreciated! Thank you so much, Sat   ... View more