Dear Michiel,

just to let you know, we have now completed the pilot study (n=56) I was asking you about (also in this thread) and I was just wondering if there is any 'benchmark' value on either t-ratios for betas or mean/se ratio, beyond which you consider the prior to be simply too unreliable to use as an input for constructing a Bayesian efficient design. We have two parameters close to 0.5 (mean/se) and one of 0.2. The latter worries me more as it is also the monetary attribute (important for estimating WTA in the final stage, hopefully). It is also the case that the estimate on the monetary attribute is negative (-.00006), but we expected to be positive as it is defined as compensation to forest owners for providing extra ecosystem services. The s-error is relatively large (app. 800) I guess due to this uncertainty (b-error seems ok, of app. 50).

I was also reading on the blog titled "Understanding S-sample output" (

http://www.choice-metrics.com/forum/vie ... ?f=2&t=969) where similar issues were discussed, but I did not see any conclusions on values of t-ratios (or mean/se) - of course if there are any.

Just for info I have copied the code with priors from the pilot study below.

Thank you!

Design

;alts=alt1, alt2, sq

;rows=18

;block=2

;eff=(mnl,d)

;alg = mfederov

;require:

sq.atr1 = 7,

sq.atr2 = 0.4,

sq.atr3 = 0,

sq.atr4 = 0.3,

sq.atr5 = 0

;model:

U(alt1) = b1[-0.00385] * atr1[7,20,34]

+ b2[-0.01320] * atr2[0.4,5,15]

+ b3.effects[-0.08044|0.23305] * atr3[1,2,0]

+ b4[0.00538] * atr4[0.3,5,20]

+ b5.effects[0.33685|0.19576] * atr5[1,2,0]

+ b6[-0.000060358] * atr6[150,300,450,600,750,900]

/

U(alt2) = b1 * atr1

+ b2 * atr2

+ b3 * atr3

+ b4 * atr4

+ b5 * atr5

+ b6 * atr6

/

U(sq) = b0[-0.93745]

+ b1 * atr1

+ b2 * atr2

+ b3 * atr3

+ b4 * atr4

+ b5 * atr5

+ b6 * atr6_sq[0]

$