Hello All,
I am using Warren Kuhfeld's excellent macros to do a conjoint design using choice experiments.
I have 4 3 level factors. I want to estimate main effects and selected interactions.
I will use 2 generic alternatives, and a "none" option which is fixed at 1,1,1,1 for the four levels.
The problem i am facing is that the design i find seems odd.
In every choice set, the levels of first factor X1 are identical for Alternatives 1 &2 in every choice set.
This should not be happening, as they should be changing too.
Any insights will be appreciated.
Here is some code and output.
Thanks
Manoj Agarwal
/* Rider Model Price 3 Wait time 3 Driver quality 3 Car quality 3*/
%mktruns(3 3 3 3,interact=x1*X2 x1*x3 x1*x4 );
/* will use the full factorial of 81 */
%mktex( 3 3 3 3,n=81,seed=100);
/* 3 options showed set the constant alternative it sets to 1 1 1 1 )*/
data final(drop=i);
set design end=eof;
retain f1-f2 1 f3 0;
output;
if eof then do;
array x[7] x1-x4 f1-f3;
do i=1 to 7;x[i] = i le 4 or i eq 7; end;
output;
end;
run;
/* after some experimentation, decided to use 18 choice sets
for the interaction design*/
%choiceff(data=final,
model=class(x1-x4)class(x1*x2 x1*x3 x1*x4/sta),
nsets=18,seed=125,maxiter=100,flags=f1-f3,options=relative nodups,beta=zero);
Block | Set | Alt | x1 | x2 | x3 | x4 |
1 | 1 | 1 | 1 | 1 | 3 | 3 |
1 | 1 | 2 | 1 | 3 | 1 | 2 |
1 | 1 | 3 | 1 | 1 | 1 | 1 |
1 | 2 | 1 | 1 | 3 | 2 | 1 |
1 | 2 | 2 | 1 | 2 | 1 | 3 |
1 | 2 | 3 | 1 | 1 | 1 | 1 |
1 | 3 | 1 | 2 | 1 | 3 | 1 |
1 | 3 | 2 | 2 | 3 | 2 | 2 |
1 | 3 | 3 | 1 | 1 | 1 | 1 |
1 | 4 | 1 | 3 | 2 | 1 | 2 |
1 | 4 | 2 | 3 | 1 | 2 | 1 |
1 | 4 | 3 | 1 | 1 | 1 | 1 |
1 | 5 | 1 | 3 | 2 | 2 | 3 |
1 | 5 | 2 | 3 | 3 | 3 | 1 |
1 | 5 | 3 | 1 | 1 | 1 | 1 |
1 | 6 | 1 | 1 | 2 | 2 | 3 |
1 | 6 | 2 | 1 | 1 | 3 | 2 |
1 | 6 | 3 | 1 | 1 | 1 | 1 |
1 | 7 | 1 | 2 | 1 | 2 | 2 |
1 | 7 | 2 | 2 | 3 | 3 | 1 |
1 | 7 | 3 | 1 | 1 | 1 | 1 |
1 | 8 | 1 | 2 | 2 | 3 | 2 |
1 | 8 | 2 | 2 | 3 | 1 | 3 |
1 | 8 | 3 | 1 | 1 | 1 | 1 |
1 | 9 | 1 | 3 | 2 | 2 | 1 |
1 | 9 | 2 | 3 | 1 | 1 | 3 |
1 | 9 | 3 | 1 | 1 | 1 | 1 |
2 | 1 | 1 | 1 | 2 | 3 | 1 |
2 | 1 | 2 | 1 | 1 | 2 | 3 |
2 | 1 | 3 | 1 | 1 | 1 | 1 |
2 | 2 | 1 | 2 | 2 | 1 | 3 |
2 | 2 | 2 | 2 | 3 | 2 | 1 |
2 | 2 | 3 | 1 | 1 | 1 | 1 |
2 | 3 | 1 | 2 | 1 | 2 | 1 |
2 | 3 | 2 | 2 | 3 | 3 | 2 |
2 | 3 | 3 | 1 | 1 | 1 | 1 |
2 | 4 | 1 | 1 | 2 | 2 | 2 |
2 | 4 | 2 | 1 | 3 | 3 | 3 |
2 | 4 | 3 | 1 | 1 | 1 | 1 |
2 | 5 | 1 | 3 | 1 | 3 | 2 |
2 | 5 | 2 | 3 | 3 | 1 | 1 |
2 | 5 | 3 | 1 | 1 | 1 | 1 |
2 | 6 | 1 | 3 | 3 | 3 | 3 |
2 | 6 | 2 | 3 | 1 | 1 | 1 |
2 | 6 | 3 | 1 | 1 | 1 | 1 |
2 | 7 | 1 | 2 | 1 | 3 | 3 |
2 | 7 | 2 | 2 | 2 | 1 | 1 |
2 | 7 | 3 | 1 | 1 | 1 | 1 |
2 | 8 | 1 | 2 | 2 | 2 | 3 |
2 | 8 | 2 | 2 | 1 | 1 | 2 |
2 | 8 | 3 | 1 | 1 | 1 | 1 |
2 | 9 | 1 | 3 | 2 | 3 | 1 |
2 | 9 | 2 | 3 | 3 | 2 | 2 |
2 | 9 | 3 | 1 | 1 | 1 | 1 |
