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Can you please explain this? Is there a parameter, a calculation which argues that this is more efficient?

Hello,

my question relates to building blocks in choice experiments.

Please imagine following scenarios:

- bayesian effcient design with 1 block including 12 choice sets, d-error=0,84
- bayesian efficient design with 2 blocks each with 12 choice sets (together 24 choice sets), d-error=0,44 ...

Is the 3 after gauss(3) saying, that there are three random parameters?

Thank you!!!!

Thank you a lot.

What I´d not understand till now is, where is the command for the rppanel in this syntax?

Michael

Thank you.

My problem is, what is the difference between mnl, rp and rppanel? And what is the best to use?

or is this a correcht bayesian sytax?

Design
;alts = alt1,alt2,alt3
;rows = 12
;eff = (rp,d,median)
;rep = 50
;rdraws = halton(100)
;model:
U(alt1) = b1[1.04] + pa[-0.07] * A[10,20,30,40] + rf.dummy[-0.28] * B[0,1] + al.dummy[(u,-9,0.33)] * C[0,1] + lf.dummy[-2.69|(u,-9.82,-0.08)|(u,-6.55,-0.4 ...

Good morning everyone,

I`ve a question relating the choice between two models for my study. I`ve created on the one hand an efficient rppanel design and on the other a bayesian rp model (a rppanel bayesian design does not work). So which one would you declare as the better alternative? Or in other ...

So would this be a suitable bayesian syntay?

Design
;alts = alt1,alt2,alt3
;rows= 12
;eff=(rp,d,median)
;rep=50
;rdraws= halton(50)
;model:
U(alt1) = b1[1.04] + pa[-0.07] * A[10,20,30,40] + rf.dummy[-0.28] * B[0,1] + al.dummy[n,(n,-4.66,1.23),(u,3.1,5.86)] * C[0,1] + lf.dummy[-2.69|n,(n,-4.97,1 ...

Thank you Michiel,

my Question is, if it`s exactly correct to use a normal distribution for dummy coded variables or if I´ve to choose something like:

b1.dummy[u,(u,0.5,0.2),(u,0.15,0.45)|...] * A[...

Regards
Micha