About Norman21

Norman21 · ‎10-10-2022

Have you had a look at this post? https://communities.sas.com/t5/ODS-and-Base-Reporting/Page-number-at-top-and-page-break-after-each-proc-report-entry/td-p/415312

Norman21 · ‎07-25-2022

Yes, this is a specific, trivial example. I'm looking for a generic solution. Perhaps a "two pass" process, where the first pass lists the "likely" merged cells. These can then be edited as required, to feed into the second pass that produces a clean result.

Norman21 · ‎07-25-2022

If you refer to the first post of this thread, I think it would be useful to have a new file output with the first variable as Continent (the merged cells). Something like this: Continent Country 1981 1982 1983 1984 Australia Australia 3.6 - - Australia New Zealand - - - Europe Austria 1.9 - - Europe Belgium 3.4 3.7 3.7 Europe Czech Republic - - - Europe Denmark 2.7 2.9 3.1 Europe Finland - - 3.9 Europe France 3.9 4.1 4.2 ...etc...

Norman21 · ‎07-24-2022

Good points. If I save the mrgcls Excel file (created by the code above) in CSV format, then open it with Notepad++, the top of the file looks like this: So could a new variable be created that flags if a row might contain merged cells, based on one or more missing data (the commas)? I could then verfity whether those rows actually contain merged cells, rather than having to look through the entire Excel file.

Norman21 · ‎07-23-2022

Thanks for this, but it seems to be a very specific solution. What I need is a general solution that will work on a variety of Excel files. Perhaps it cannot be done in SAS.

Norman21 · ‎05-17-2022

But that doesn't answer the question! Smoking Status status2 sex2 bp_status2 Heavy (16-25) Light (1-5) Moderate (6-15) Non-smoker Very Heavy (> 25) Alive Female High 5927 10343 6070 56997 1105 Alive Female Normal 12955 17817 12365 59314 2040 Alive Female Optimal 6859 7945 7402 23389 1584 Alive Male High 14695 3485 4996 25251 8327 Alive Male Normal 21304 4603 6685 24049 11241 Alive Male Optimal 6489 1414 2826 6839 3159 Dead Female High 6954 7483 5694 50404 2200 Dead Female Normal 4144 4518 4438 16531 951 Dead Female Optimal 2021 1848 1629 3044 584 Dead Male High 20820 5698 6990 26980 15744 Dead Male Normal 14253 2775 5176 14331 7770 Dead Male Optimal 4242 451 940 2494 1337

Norman21 · ‎05-16-2022

It ain't pretty but is this what you mean? proc report data=sashelp.heart split='~' nowd ; column status status2 sex sex2 bp_status bp_status2 outcomes MRW,Smoking_Status; define Smoking_Status / Across; define status / Group noprint; define sex / Group noprint; define bp_status / Group noprint; define MRW / sum ''; define status2 / computed; define sex2 / computed; define bp_status2 / computed; define outcomes / computed; compute before bp_status; _status=status; _sex=sex; _bp_status=bp_status; endcomp; compute status2/character length=40; status2=_status; endcomp; compute sex2/character length=40; sex2=_sex; endcomp; compute bp_status2/character length=40; bp_status2=_bp_status; endcomp; compute outcomes ; outcomes = 1 ; endcomp; run;

Norman21 · ‎11-28-2021

In the penultimate line of your code, try: output out= EMpull2 (rename=(sum=QTR_COST real_date=year_qtr) ) ;

Norman21 · ‎11-05-2021

You can change the page height as follows: ods excel file = "C:\My SAS\_examples_\Example.xlsx" options(ROWBREAKS_COUNT='25'); proc print data=sashelp.cars; run; ods excel close ; You can see the effect of changing ROWBREAKS_COUNT in Excel by selecting View, Page Break Preview:

Norman21 · ‎11-05-2021

Welcome to the Community! You might find the following helpful: https://blogs.sas.com/content/iml/2011/09/19/count-the-number-of-missing-values-for-each-variable.html

Norman21 · ‎08-04-2021

This might help: https://blogs.sas.com/content/iml/2016/03/09/comparative-panel-overlay-histograms-sas.html

Norman21 · ‎08-04-2021

You might want to consider a non-parametric equivalent of the 2-way ANOVA, such as the Friedman test, as described on this page: https://stats.idre.ucla.edu/sas/whatstat/what-statistical-analysis-should-i-usestatistical-analyses-using-sas/

Norman21 · ‎07-28-2021

Following on from the idea of FreelanceReinhard and using the code from one of Sanjay Matange's blogs (https://blogs.sas.com/content/graphicallyspeaking/2018/02/19/survival-plot-twist-using-sgplot-procedure/) you can produce something like this: title 'Product-Limit Survival Estimates'; footnote j=l h=6pt italic 'This visual is for discussion of graph features only.' ' The actual details should be customized by user to suit their application.'; data my; input time surv1 surv2 surv3 surv4 ; label time='Survival Time (days)' surv1='Group 1' surv2='Group 2' surv3='Group 3' surv4='Group 4' ; cards; 0 1 1 1 1 0 1 0.993631 1 0.965475 1 1 0.980955 1 0.954309 2 1 0.968365 1 0.941546 3 1 0.962017 1 0.931951 4 0.990686 0.962017 0.989159 0.927144 5 0.990686 0.962017 0.989159 0.922343 6 0.981322 0.955658 0.957124 0.908054 7 0.981322 0.955658 0.946394 0.900084 345 0.612125 0.774457 0.574568 0.592467 350 0.612125 0.774457 0.574568 0.590918 355 0.612125 0.774457 0.574568 0.589368 356 0.612125 0.767991 0.574568 0.589368 360 0.612125 0.761524 0.574568 0.589368 ; proc sgplot data=my noborder; step x=time y=surv1 / ; step x=time y=surv2 / ; step x=time y=surv3 / ; step x=time y=surv4 / ; run;

Norman21 · ‎07-27-2021

I suppose it depends on your hypothesis - all three groups are the same, or all three groups are different, or one group is different from the other two...? The following describes running simulations, you might find this helpful: https://www.lexjansen.com/pharmasug/2004/StatisticsPharmacokinetics/SP08.pdf Also this, especially the example: https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.4780142010

Norman21 · ‎06-19-2021

I think the explanation is in the sentence on the top of page 12 "The output layout has a better appearance in the Excel destination, too, because cells are passed to a routine that measures and resizes columns for optimal display."

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