I am a beginner in SAS.
I do not know how to keep all of my regression estimates in order to do my PROC test below.
Ultimately, I would like to compare 2 by 2 all of my 10 models by testing each time whether the 2 intercepts are statistically the same or not. That's why I prefer to compute delta before.
But the trouble is I have 12 main comparisons of these models to do and I don't want to write manually each estimate to compute my delta for each comparison.
Can you help me to write a code in order to link automatically my PROC test and all the regression estimates I need to compute my delta ?
proc format;
picture stderrf (round)
low-high=' 9.99)' (prefix='(')
.=' ';
run;
ods output ParameterEstimates (persist) = t;
proc reg data = modelization ;
M1: model rp=rm;
MFS1: model rp=rm rm_zdy rm_ztbl rm_ztms rm_zdfy;
M2: model rp=rm rmrsq;
MFS2: model rp=rm rm_zdy rm_ztbl rm_ztms rm_zdfy rmrsq;
MPM10: model rp=rm rm_pred_mean;
MPM11: model rp=rm rm_pred_mean rmrsq;
MCFG1: model rp=rm zdy ztbl ztms zdfy rm_zdy rm_ztbl rm_ztms rm_zdfy;
MCFG2: model rp=rm zdy ztbl ztms zdfy rm_zdy rm_ztbl rm_ztms rm_zdfy rmrsq;
MPM20: model rp=pred_mean rm rm_pred_mean;
MPM21: model rp=pred_mean rm rm_pred_mean rmrsq;
run;
ods output close;
proc print data=t;
run;
proc tabulate data=t noseps;
class model variable;
var estimate stderr;
table variable=''*(estimate =' '*sum=' '
stderr=' '*sum=' '*F=stderrf.),
model=' '
/ box=[label="Parameter"] rts=15 row=float misstext=' ';
run;
/*Example of only 1 comparison by computing delta: difference of intercepts to make a test of significativity */
data modelization;
set modelization;
intercept23 = rp + 0.27098*rm + 0.001889*zdy - 0.12634*ztbl - 0.23400*ztms - 0.38475*zdfy + 0.27095*rm_zdy + 6.88259*rm_ztbl + 3.89297*rm_ztms - 0.72923*rm_zdfy + 0.73268*rmrsq;
intercept24 = rp + 0.10546*rm + 1.68536*pred_mean + 6.90634*rm_pred_mean + 0.26742*rmrsq;
delta12 = intercept23-intercept24;
run;
proc univariate data=modelization;
var delta12;
run;
