Hi,
I am designing a DCE pilot test and would appreciate your expertise before I run it. The target sample are prostate cancer patients who have been treated with radiotherapy, and the goal is to determine the MRS for short (b4, levels in %) and long (b5, levels in %) term side effects, and chance of cancer recurrence (b3, levels in %) compared to length of treatment (b1, in weeks). We are hoping to determine what risk of side effects patients are willing to risk for shorter treatment time. b2 is a binary attribute for if an extra procedure is required prior to radiation (yes is 1). This DCE is unlabelled and I excluded the constant based on one of the moderators comments I read on a different post. All the coefficients are negative because the lower percentage risk, shorter treatment time, and no prior procedure should be preferred.
I have the following syntax:
Design
?pilot test, WTP denominator constant, S estimate: n min 55
;alts = alt1*, alt2*
;rows = 24
;eff = (mnl,wtp(wtp1),mean)
;rep = 500
;rdraws = halton(250)
;wtp = wtp1(b3,b4,b5/b1)
;block = 2
;model:
U(alt1) = b1[-0.5] * A[2,4,8] + b2[-0.2] * B[0,1] + b3[(n,-0.3,0.1)] * C[6,12,18] + b4[(n,-0.2,0.1)] * D[20,35,50] + b5[(n,-1.2,0.2)] * E[10,15,20] /
U(alt2) = b1 * A + b2 * B + b3 * C + b4 * D + b5 * E
$
There are previous published DCEs for prostate cancer patients which is where I found the priors, though the definitions of the attributes do not exactly match mine. Questions I have:
1. Is it best to use bayesian mnl for the design since I do not know the exact parameter values? I also don't know if they are normally distributed. Or should I just used fixed values? Does this influence if I can analyze the data with conditional, mixed, bayesian, or latent class logit?
2. A small sample size <60 is likely, for the S generated values by NGene should I be multiplying that by 2 since I have 2 blocks? So I should try to find a design with S< 30?
3. Would you suggest eff by d or WTP?
4. Covariates- do I need to include these in the design stage or can I analyze for subgroups/ preference heterogeneity afterwards? I know my sample size will be small so may not be possible to do subgroup analysis. I am interested if distance from cancer centre, employment status, and age are interacting with preference for length of treatment.
5. To analyze the results of my pilot study (and eventual main DCE) I plan on using SAS as that is free for me. I was going to use conditional logit (MNL) to find the parameters from my pilot test (n=5) and then use these new values to make a new design for my DCE. Does this sound correct?
Thank you very much for your time and expertise!
Sam