Estimating standard error of differences dynamically

[brophymj]

Hi

I have a number of factors in my dataset and each factor has a number of levels. What I want to achieve is shown below. My code performs a proc genmod on the dataset for each factor which produces the first 2 tables below to a dataset. The first table shows the correlation matrix for one of the factors (which has 6 levels); the second dataset shows the parameter estimates and standard errors for each of the parameters.  

I want the code to loop through each combination of paramters (there are 15 combinations) and calculate the standard error of the differences and output the results to a table like the last time shown below. The formula for the standard error of differences I am using is:

Std(p1-p2) = sqrt[ Std(p1)^2 + Std(p2)^2 - 2*Std(p1)*Std(p2)*corr(p1,p2) ]

Then this is divided by the difference in the two paramters

so Std(p1-p2)/(p1-p2)

I've tried using contrast and other statements but I need it to be this exact formula and to be able to create a macro that performs this for difference factors with difference number of levels.

Correlation Matrix

RowName	Prm1	Prm2	Prm3	Prm4	Prm5	Prm6
Prm1	1	-0.1487	-0.0531	-0.11	-0.2161	-0.1575
Prm2	-0.1487	1	0.0079	0.0163	0.0321	0.0234
Prm3	-0.0531	0.0079	1	0.0058	0.0115	0.0084
Prm4	-0.11	0.0163	0.0058	1	0.0238	0.0173
Prm5	-0.2161	0.0321	0.0115	0.0238	1	0.034
Prm6	-0.1575	0.0234	0.0084	0.0173	0.034	1

Paramter Estimates

RowName	Estimates	Std Error
Prm1	0	0
Prm2	-0.0086	0.428094
Prm3	0.077144	1.199069
Prm4	-1.28369	0.578712
Prm5	0.206858	0.294558
Prm6	0.498941	0.404168

Standard Error of Differences

RowName	Prm1	Prm2	Prm3	Prm4	Prm5	Prm6
Prm1
Prm2
Prm3	1481%
Prm4
Prm5
Prm6

Standard Error of Differences
Factor 1	Factor 2	Std Diff (%)
Prm1	Prm1	…
Prm1	Prm2	…
Prm1	Prm3	1481%
Prm1	Prm4	…
Prm1	Prm5	…
Prm2	Prm2	…
Prm2	Prm3	…
Prm2	Prm4	…
Prm2	Prm5	…
Prm3	Prm3	…
Prm3	Prm4	…
Prm3	Prm5	…
Prm4	Prm4	…
Prm4	Prm5	…
Prm5	Prm5	…

My proc genmod code that produces the correlation and paramter estimates table is shown below.  

proc genmod data=insurancedata;

class glm31_cover_type(ref="COMP");

Weight NbClaims;

model AvgClaim = glm31_cover_type/ dist=gamma link=log obstats SCALE=DEVIANCE CORRB;

ods output ParameterEstimates =myObStats CORRB = CorrMatrix;

run;

 I have attached my dataset.

[Ksharp]

Once you get Paramter Estimates and their Std Errors as you showed
You can use proc transpose firstly to get like:

Prm1	Prm2	Prm3	Prm4	Prm5	Prm6
0           0.428094    1.19 ..........

and use data step (double loop) to get what you want;

data want;
 set have;
 array x{*} prm1-prm6;
  do i=1 to dim(x)-1;
   do j=i+1 to dimx(x);
     vname1=vname(x{i});
     vname2=vname(x{j});
     ..........your function of STD ...........
    output;
  end;
end;
run;