by prefer » Wed Oct 08, 2014 6:18 pm
Dear Michiel,
Thank you for the advice and I realize the problem. I am just making the design just using my own priors to make simulation, and as you said the priors are not reliable and I can see that when I change the priors. The design will be used for a pilot study and for that I will use 0 as a prior and then use the results from the pilot as priors to produce the final design.
However, we decided to make the amount attribute continuous and investigate the linear relationship, simply because it doesn't make sense to make the amount attribute dummy/effects coded variable while it is a continuous variable - it is continuous in a sense that its levels are 250g,150g,50g,and 0g. So what I am thinking now is to use 1,2,3,4 as levels of the amount attribute in the design and replace these levels with 250,150,50 and 0 later on as it is commonly done when designing a DCE. Do you see any problem in doing that?
For you information, I got the following design (the design code is copied) but I am a little bit suspicious of the choice probabilities. Do you think they are OK? And attribute level 1 is identical in choice situation 2 and 6 for the amount attribute? I don't think that a problem but do you see any noise? Thank you indeed for your time!!
Design
; alts = alt1, alt2, alt3
; rows = 12
; eff = (mnl,d)
; Model :
U(alt1) = amo[0.95]*amount[1,2,3,4]+cost[-0.006]*price[35,37,39,43,44,47]/
U(alt2) = amo*amount+cost*price$
MNL efficiency measures
D error 0.011823
A error 0.089087
B estimate 25.032272
S estimate 105.201374
Prior amo cost
Fixed prior value 0.95 -0.006
Sp estimates 0.754224 105.201374
Sp t-ratios 2.256867 0.191093
Design
Choice situation alt1.amount alt1.price alt2.amount alt2.price
1 3 39 1 43
2 1 47 1 44
3 2 39 4 37
4 1 43 3 39
5 4 35 3 44
6 1 44 1 47
7 4 37 2 39
8 2 47 3 35
9 3 44 4 35
10 4 37 2 43
11 3 35 2 47
12 2 43 4 37
MNL probabilities
Choice situation alt1 alt2 alt3
1 0.820266 0.119777 0.059957
2 0.395117 0.402293 0.20259
3 0.125697 0.850546 0.023757
4 0.119777 0.820266 0.059957
5 0.717355 0.262847 0.019798
6 0.402293 0.395117 0.20259
7 0.850546 0.125697 0.023757
8 0.251443 0.698697 0.04986
9 0.262847 0.717355 0.019798
10 0.853088 0.123084 0.023828
11 0.698697 0.251443 0.04986
12 0.123084 0.853088 0.023828