Number of rows? Bayesian vs. zero priors?
Posted: Thu Jul 18, 2019 12:08 am
Hi there! I'm new to Ngene, so I wanted to make sure that I'm doing this right. I'm designing a DCE with 6 attributes (2 with 3 levels, 4 with 2 levels). Each participant will be presented with 11 choice sets. I don't have any pilot data, so I was trying out zero priors and Bayesian priors for the first participants and then adjusting the priors based on those initial results. Here is the code I've worked with so far:
0 priors:
Design
;alts = alt1, alt2
;rows = 66
;block = 6
;eff = (mnl,d)
;model:
U(alt1)=b1[0]*A[-1,0,1]+ b2[0]*B[-1,0,1] + b3[0]*C[-1,1] + b4[0]*D[-1,1] +
b5[0]*E[-1,1] + b6[0]*F[-1,1] /
U(alt2)=b1*A + b2*B + b3*C + b4*D + b5*E + b6*F
$
Bayesian priors:
Design
;alts = alt1, alt2
;rows = 66
;block = 6
;eff = (mnl,d)
;model:
U(alt1)=b1[(u,-1,1)]*A[-1,0,1]+ b2[(u,-1,1)]*B[-1,0,1] + b3[(u,-1,1)]*C[-1,1] + b4[(u,-1,1)]*D[-1,1] +
b5[(u,-1,1)]*E[-1,1] + b6[(u,-1,1)]*F[-1,1] + b7[(u,-1,1)]*G[-1,1] /
U(alt2)=b1*A + b2*B + b3*C + b4*D + b5*E + b6*F + b7*G
$
Here are my questions:
1. How should the number of rows be determined? I know that it has to be divisible by 2 and 3 (the number of levels), so I just multiplied by 11 (number of choice sets per participants), but that feels random. Is there a benefit to having more rows and more blocks? The total sample size of our study is 136, so with 66 rows, ~23 people will be answering each block.
2. Do you recommend using 0 priors or Bayesian before we have actual priors from pilot data?
3. Does everything else seem right?
Thank you so much for your help! I am very appreciative.
0 priors:
Design
;alts = alt1, alt2
;rows = 66
;block = 6
;eff = (mnl,d)
;model:
U(alt1)=b1[0]*A[-1,0,1]+ b2[0]*B[-1,0,1] + b3[0]*C[-1,1] + b4[0]*D[-1,1] +
b5[0]*E[-1,1] + b6[0]*F[-1,1] /
U(alt2)=b1*A + b2*B + b3*C + b4*D + b5*E + b6*F
$
Bayesian priors:
Design
;alts = alt1, alt2
;rows = 66
;block = 6
;eff = (mnl,d)
;model:
U(alt1)=b1[(u,-1,1)]*A[-1,0,1]+ b2[(u,-1,1)]*B[-1,0,1] + b3[(u,-1,1)]*C[-1,1] + b4[(u,-1,1)]*D[-1,1] +
b5[(u,-1,1)]*E[-1,1] + b6[(u,-1,1)]*F[-1,1] + b7[(u,-1,1)]*G[-1,1] /
U(alt2)=b1*A + b2*B + b3*C + b4*D + b5*E + b6*F + b7*G
$
Here are my questions:
1. How should the number of rows be determined? I know that it has to be divisible by 2 and 3 (the number of levels), so I just multiplied by 11 (number of choice sets per participants), but that feels random. Is there a benefit to having more rows and more blocks? The total sample size of our study is 136, so with 66 rows, ~23 people will be answering each block.
2. Do you recommend using 0 priors or Bayesian before we have actual priors from pilot data?
3. Does everything else seem right?
Thank you so much for your help! I am very appreciative.