I am trying to ensure I am going about this right. Here is a very brief description. I have:

Att1 Infection status [0,1,2]

Att2 Seller [0,1,2]

Att3 Price [4000,5500,9,000,14000]

Step 1: For pilot study

Generate efficient design with zero priors and some signs known.

Att1 Inf. status: ( + )infection free, (unknown sign) infection take care, ( - )infected]

Att2 Seller: no idea about priors

Att3 price should be negative but do I need to have effects/dummy coding since I don't have the best guesses for each of the priors?

- Code: Select all

?Auction designpilot

Design

;alts = alt1, alt2, alt3

?alt3 neither

; rows = 18

; block = 3

; eff = (mnl, d)

;cond:

if(alt1.status = [0] and alt1.price =[4000] and alt1.seller =[0], alt2.status = [0,1,2] and alt2.price = [4000] and alt2.seller =[0,1,2])

;con

; model:

?seller #, status#, price#

U(alt1) = b2*seller[0,1,2] + b3.effects[0.0001|-0.0001]*status[0,1,2] + b4[-0.0001]*price[4000, 5500, 9000, 14000]/

U(alt2) = b2*seller + b3*status + b4*price/

U(alt3) = b5

?

$

Step 2:

Run pilot, estimate for MNL.

Step 3: Actual final study

Use priors and SE’s from pilot to design Bayesian efficient design [n, mean,se].

BUT, if I want to estimate a mixed logit model, then I optimise for mnl and evaluate for panel mixed logit:

Like so?

- Code: Select all
`?Auction design`

Design

;alts(mnl_model) = alt1, alt2, alt3

;alts(rpl_model) = alt1, alt2, alt3

?alt3 neither

; rows = 18

; block = 3

; eff = mnl_model(mnl, d)

;rdraws = gauss(3)

,rep = 500

;cond:

if(alt1.status = [0] and alt1.price =[4000] and alt1.seller =[0], alt2.status = [0,1,2] and alt2.price = [4000] and alt2.seller =[0,1,2])

;con

; model(mnl_model):

?seller #, status#, price#

U(alt1) = b2[prior]*seller[0,1,2] + b3.effects[0.0001|-0.0001]*status[0,1,2] + b4[-0.0001]*price[4000, 5500, 9000, 14000]/

U(alt2) = b2*seller + b3*status + b4*price/

U(alt3) = b5

;model(rpl_model):

U(alt1) = b2[n,prior,sd]*seller[0,1,2] + b3.effects[n,prior|prior,sd|sd]*status[0,1,2] + b4[n,prior,sd]*price[4000, 5500, 9000, 14000]/

U(alt2) = b2*seller + b3*status + b4*price/

U(alt3) = b5

$

In the rpl_model, have I coded this correctly for effects coding with bayesian priors?

Is this procedure correct?

Any feedback would be greatly appreciated.

Apologies if my questions are stupid, just never did this before.

Thank you,