I have need the last modification in my proc programming that can also estimate the 95% CI (Confidence Interval), though my proc programming estimate 95% CL but I need 95% CI (Confidence Interval).
data exp;
set geumar2;
if expno=1;
run;
;
proc nlin data=exp method=marquardt;
parms B=0.5 R=0.1;
delta=0.000001;
s=sow**(1-B)-R*(1-B)*time;
if s>0 then stx=s**(1/(1-B));
else stx=0;
model stw=stx;
sb=(sow**(1-B+delta)-R*(1-B+delta)*time);
if sb>0 then sdb=(stx-sb**(1/(1-B+delta)))/delta;
else sdb=0;
der.B=sdb;
sr=(sow**(1-B)-(R-delta)*(1-B)*time);
if sr>0 then sdr=(stx-sr**(1/(1-B)))/delta;
else sdr=0;
der.R=sdr;
output out=expp p=pstw r=stw_residual;
run;
proc summary data=expp;
var stw_residual stw;
output out=stats css(stw)=sstot uss(stw_residual)=ssres N=N;
run;
data expp;
set stats;
rsquared=1-(ssres/sstot);
adjrsquared = 1-(1-rsquared)*(N-1) / (N- 2 -1);
run;
proc print data=expp;
run;
SAS Innovate 2025 is scheduled for May 6-9 in Orlando, FL. Sign up to be first to learn about the agenda and registration!
ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.
Find more tutorials on the SAS Users YouTube channel.