I just finished the pilot survey and want to proceed to the final experiment.

I plan to analyze the data using a mixed logit model. The experiment includes three labeled alternatives, and based on the literature, I thought about 30 rows divided into five blocks such that each respondent gets six choice tasks.

This is the model I came up with:

- Code: Select all
`Design`

;alts=evening, night, noon

;rows=30

;block=5

;eff=(rp,d)

;cond:

if(noon.work=0, noon.limitations=0),

if(noon.work=1, noon.day=0)

;model:

U(noon)= b1[-0.837] +

b2.dummy[-0.228] * work[1,0] +

b3.dummy[n,0.201,0.822] * day[1,0] +

b4.effects[-0.323|-0.147] * limitations[2,1,0] +

b5.dummy[0.010] * green[1,0] +

b6[-0.015] * weeklycost[20:50:10] /

U(evening)=b3 * day +

b6 * weeklycost1[80:110:10] /

U(night)= b8[-0.751] +

b3 * day +

b7.effects[-0.841|-0.946|-0.394] * limitations2[5,4,3,0] +

b6 * weeklycost2[50:80:10]

$

I think the only coefficient I should treat as random is “day,” as it is the only coefficient with a significant SD in the pilot results. However, I can also treat “work” and “green” as random, which yields different designs with the following characteristics:

Day+work+green random: d-error= 0.871, S estimate=59663

Day+work random: d-error=0.51, S estimate=924

Day random (the design in the code above): d-error=0.31, S estimate=25886

My questions are:

1. Do I need to choose the design with the smallest d-error?

2. Is the d-error I get too high? What would be a reasonable d-error?

3. How should I interpret the S estimate in terms of sample size? Does 25K mean I should sample 25K people (N=25K)? Or is it the number of choice tasks (N*6=25K) or the number of observations (N*6*3)?

4. Is there anything I can do to improve this design?

5. BTW, how do you apply a non-significant coefficient from the pilot study as a prior in the final design? Should I use its non-significant coefficient or zero?

Many thanks in advance!

A.