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Graphics in SAS SGPLOT illustrating ANOVA analysis results.

Output and graphics from statistical programming packages are often time-consuming to read and interpret. In peer-reviewed publications you usually provide both a written assessment, tables and graphics illustrating data and analysis results. ANOVA analysis is still a very common analysis technique and it is possible to beautify the output from analysis using PROC SGPLOT

ods graphics; proc format lib=work; value timevar 12=’0-12 hrs’ 18=’12-18 hrs’ 24=’18-24 hrs’ 32=’Cumulated 0-24 hrs’ ; run; proc sql;   create table estimates     (  Treatment char(12) label=’Treatment Group’      , Time      num      label=’Visit number’      , Time2     num      label=’Visit number’      , TimeVar   char(18) label=’Visit number’      , Mark      char(8)  label=’p values’      , Est       num      label=’Est’      , LCL       num      label=’LCL’      , UCL       num      label=’UCL’     )   ; insert into estimates values(‘Control’, 12, 12,  ‘0-12 hrs’, ”,87.5000,65.9552,109.0448) values(‘Control’, 18, 18, ’12-18 hrs’, ”,23.1250,15.7518,30.4982) values(‘Control’, 24, 24, ’18-24 hrs’, ”,16.8750,10.3570,23.3930) values(‘Control’, 32, .,’Cumulated 0-24 hrs’, ”,127.7083,101.1505,154.2661) values(‘Intervention’, 12, 12, ‘0-12 hrs’, ‘p=0.0159’,50.0000,28.4552,71.5448) values(‘Intervention’, 18, 18, ’12-18 hrs’, ‘p=0.0256’,11.2500,3.8768,18.6232) values(‘Intervention’, 24, 24, ’18-24 hrs’, ‘p=0.0462’,7.5000,0.9820,14.0180) values(‘Intervention’, 32, .,’Cumulated 0-24 hrs’, ‘p=0.0023’,69.3750,42.8172,95.9328)   ; quit; title ‘Morphine consumption during postop’; proc sgplot data=estimates;   format Time Time2 timevar.;   scatter x=Time y=est / yerrorlower=LCL yerrorupper=UCL group=Treatment groupdisplay=cluster clusterwidth=0.2 errorbarattrs=(thickness=1) datalabel=Mark DATALABELPOS=BOTTOMRIGHT DATALABELATTRS=(color=BLACK);   series  x=Time2 y=est / lineattrs=(pattern=solid) group=Treatment groupdisplay=cluster clusterwidth=0.2 lineattrs=(thickness=2) name=’s’;   yaxis label=’Mean with 95% CL’ grid;   xaxis display=(nolabel);   keylegend ‘s’ / title=’Treatment’; run; proc sgplot data=estimates;   format Time Time2 timevar.;   scatter x=Time y=est / yerrorlower=LCL yerrorupper=UCL group=Treatment groupdisplay=cluster clusterwidth=0.2 errorbarattrs=(thickness=1) DATALABELPOS=BOTTOMRIGHT DATALABELATTRS=(color=BLACK);   series  x=Time2 y=est / lineattrs=(pattern=solid) group=Treatment groupdisplay=cluster clusterwidth=0.2 lineattrs=(thickness=2) name=’s’;   yaxis label=’Mean with 95% CL’ grid;   xaxis display=(nolabel); run;







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