Help with partial choice set designs
Posted: Thu Oct 07, 2021 12:07 am
Dear Michiel,
I am trying to generate a partial choice set design following the method in the section 8.11 of the Ngene Manual. However, I have a couple of doubts which I could not resolve by myself.
1) Is there any limit for the total number of alternatives? I mean, would it be ok to apply such method with, for example, 15 alternatives?
2) How does the candidate set design is specifically created? The Manual says that it can be created in Excel, R, or Matlab. Thus, I imagine that a complete candidate set is created outside Ngene. Also, the Manual says that in the case of complete candidate set be very large, one can use an incomplete design with a random selection of 1% of all possible choice tasks. Thus, I imagine that I should first create the complete candidate set and then sample a subset from that (e.g., 1%). Because it is not clear to me this process, I would really appreciate if you could check the steps below (or even share a reproducible example from R):
GENERATING THE CANDIDATE SET DESIGN IN R
a. Generate a complete design
b. Random select 1% of all possible choice tasks
c. Evenly randomly alocate 999 across the attributes
GENERATING THE PARTIAL CHOICE SET DESIGN IN NGENE
d. Finally, generate the partial choice set in NGENE using a synthax such as
Design
;alts = car, train, bus, tram, bike
;rows = 15
;eff = (mnl,d)
;alg = mfederov(candidates = partial_choice_sets.csv)
;model:
U(car) = b1[0.3] +
b2[-0.05] * ctime[15,20,25,999] +
b3[-0.3] * fuel[1,2,999] +
b4[-0.4] * toll[0,1,999] /
U(train) = b5[0.2] +
b6[-0.04] * ttime[10,15,20,999] +
b7[-0.08] * accegg[5,10,15,999] +
b8[-0.08] * transfer[0,5,10,999] +
b9[-0.3] * fare[2,3,999] /
U(bus) = b10[-0.2] +
b11[-0.06] * btime[15,20,25,999] +
b7 * accegg +
b8 * transfer +
b9 * fare2[1,2,999] /
U(tram) = b12[0.1] +
b6 * ttime +
b7 * accegg +
b8 * transfer +
b9 * fare2 /
U(bike) = b13[-0.08] * biketime[20,30,40,999]
$
Does it sound correctly?
3) Does this method work for experiments in which the quantity of alternatives vary across choice sets? For example, I would like to show choice sets varying between four, five, and six alternatives rather than to show a fixed number (e.g., four alternatives per choice set). If yes, is there any special procedure in the candidate set design generation?
Thank you very much for your time!
Best, Rafael Lionello.
I am trying to generate a partial choice set design following the method in the section 8.11 of the Ngene Manual. However, I have a couple of doubts which I could not resolve by myself.
1) Is there any limit for the total number of alternatives? I mean, would it be ok to apply such method with, for example, 15 alternatives?
2) How does the candidate set design is specifically created? The Manual says that it can be created in Excel, R, or Matlab. Thus, I imagine that a complete candidate set is created outside Ngene. Also, the Manual says that in the case of complete candidate set be very large, one can use an incomplete design with a random selection of 1% of all possible choice tasks. Thus, I imagine that I should first create the complete candidate set and then sample a subset from that (e.g., 1%). Because it is not clear to me this process, I would really appreciate if you could check the steps below (or even share a reproducible example from R):
GENERATING THE CANDIDATE SET DESIGN IN R
a. Generate a complete design
b. Random select 1% of all possible choice tasks
c. Evenly randomly alocate 999 across the attributes
GENERATING THE PARTIAL CHOICE SET DESIGN IN NGENE
d. Finally, generate the partial choice set in NGENE using a synthax such as
Design
;alts = car, train, bus, tram, bike
;rows = 15
;eff = (mnl,d)
;alg = mfederov(candidates = partial_choice_sets.csv)
;model:
U(car) = b1[0.3] +
b2[-0.05] * ctime[15,20,25,999] +
b3[-0.3] * fuel[1,2,999] +
b4[-0.4] * toll[0,1,999] /
U(train) = b5[0.2] +
b6[-0.04] * ttime[10,15,20,999] +
b7[-0.08] * accegg[5,10,15,999] +
b8[-0.08] * transfer[0,5,10,999] +
b9[-0.3] * fare[2,3,999] /
U(bus) = b10[-0.2] +
b11[-0.06] * btime[15,20,25,999] +
b7 * accegg +
b8 * transfer +
b9 * fare2[1,2,999] /
U(tram) = b12[0.1] +
b6 * ttime +
b7 * accegg +
b8 * transfer +
b9 * fare2 /
U(bike) = b13[-0.08] * biketime[20,30,40,999]
$
Does it sound correctly?
3) Does this method work for experiments in which the quantity of alternatives vary across choice sets? For example, I would like to show choice sets varying between four, five, and six alternatives rather than to show a fixed number (e.g., four alternatives per choice set). If yes, is there any special procedure in the candidate set design generation?
Thank you very much for your time!
Best, Rafael Lionello.