Hello fellow statlisters:
I am seeking advice on an analysis of paired choice data measured via
a public survey. A fractional factorial design was used to generate
the paired choice experiment - 6 attributes, each with 3 levels; main
effects only design. The 18 choice set design was blocked into two
survey versions so that each respondent was asked to evaluate 9 paired
choice sets. Survey versions were administered randomly.
The form of the data are as in the matrix below, with:
ID = respondent ID
QS = paired choice set ID
Scenario = 1 for option A, 2 for option B in choice set
Attribute 1 = value (level) of attribute 1 in corresponding option
Attribute 2 = value (level) of attribute 2 in corresponding option
.
.
.
Attribute 6 = value (level) of attribute 6 in corresponding option
Thus, for each respondent, there are 18 rows of data ? one row for
each option of each of the 9 paired choice sets. Because I have
repeated measures (i.e., multiple choice set observations from each
respondent), I estimated a conditional logit (panel data estimator)
using the clogit command. However, I am seeking clarification and
guidance as to whether the clogit or the asclogit is the more
appropriate analysis procedure for my data, given that they include
multiple observations from individual respondents and are formatted
such that each choice set observation is entered as two rows of data
that should be processed together.
ID QS Scenario Choice Attribute 1 Att 2 Att 3 Att 4 Att 5 Att 6
1 1 1 1 1 1 1 1 1 1
1 1 2 1 2 1 3 1 2 1
1 2 1 0 1 1 1 3 2 2
1 2 2 1 2 2 2 2 1 3
1 3 1 0 1 2 1 1 1 1
1 3 2 1 1 1 3 1 2 2
1 4 1 1 3 3 1 2 1 1
1 4 2 0 1 1 2 2 1 2
1 5 1 1 1 2 1 3 3 3
1 5 2 1 3 3 3 1 2 2
1 6 1 0 2 1 1 3 2 1
1 6 2 0 1 3 3 1 1 3
1 7 1 1 1 3 2 2 1 3
1 7 2 1 2 2 1 3 3 2
1 8 1 0 3 2 3 2 3 3
1 8 2 0 1 1 2 1 2 1
1 9 1 1 2 3 1 1 1 3
1 9 2 1 1 2 1 3 2 1
Any suggestions would be greatly appreciated!
Thanks,
-Carena
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