Hello,
I would like parameters' names (or labels) to be shown in the Covariance (CovB) and Correlation (CorrB) matrix when I use the GENMOD procedure. In effect I only see prm1, prm2, etc... and if I use several covariates in the model I struggle to find out which parameter is correlated to another parameter.
Does anyone know how to achieve it?
Thank you
EG
Some post processing of the table data can yield a more informative correlation matrix. Starting with the logistic regression from the doc:
data drug;
input drug$ x r n @@;
datalines;
A .1 1 10 A .23 2 12 A .67 1 9
B .2 3 13 B .3 4 15 B .45 5 16 B .78 5 13
C .04 0 10 C .15 0 11 C .56 1 12 C .7 2 12
D .34 5 10 D .6 5 9 D .7 8 10
E .2 12 20 E .34 15 20 E .56 13 15 E .8 17 20
;
proc genmod data=drug;
class drug;
model r/n = x drug / dist = bin
link = logit
lrci corrb;
ods output parmInfo=pi corrb=cb;
run;
data pi2;
set pi;
length label $32;
label = catx("=", Effect, drug);
run;
proc sql;
select catx("=", parameter, quote(trim(label)))
into :labels separated by " "
from pi2;
quit;
data cb2;
set cb(rename=rowname=parameter); set pi2; by parameter notsorted;
label &labels.;
run;
title "Correlation between parameter estimates";
proc print data=cb2 label noobs; var label prm: ; run;
Correlation between parameter estimates label Intercept x drug=A drug=B drug=C drug=D Intercept 1.0000 -0.7550 -0.3098 -0.3787 -0.1956 -0.2279 x -0.7550 1.0000 0.0181 -0.0880 -0.1000 -0.1920 drug=A -0.3098 0.0181 1.0000 0.3050 0.1849 0.2533 drug=B -0.3787 -0.0880 0.3050 1.0000 0.2895 0.4030 drug=C -0.1956 -0.1000 0.1849 0.2895 1.0000 0.2543 drug=D -0.2279 -0.1920 0.2533 0.4030 0.2543 1.0000
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