Dear all,
I hope my question is not too far outside the scope of this forum. I recently conducted a Best-Worst (Case 1) choice experiment. I am familiar with how to implement the “Count” method (Best minus Worst) but would like to run a more in-depth analysis, such as a conditional logit or latent class logit model. I am having issues with coding my dataset to allow me to do this.
Suppose I have 6 attributes (A, B, C, D, E, F) of interest. I provide participants 10 choice scenarios, with each scenario including only 3 of the attributes. How do I go about creating a dataset that will allow me to run a conditional logit or latent class logit model from the participants’ responses? Below is an example of a dataset I created but when I run a conditional logit, the last variable (e.g., F) is omitted due to collinearity. In this example, choice scenario #1 (of 10) asks participants to select a Best/Worst combo between {A, B, F}. For sake of brevity, I am only including the data related to the first choice scenario. The remaining 9 scenarios for each respondent would be coded similarly. The dependent variable in this example is “Choice” with A, B, C, D, E, and F being the independent variables. In scenario #1, the participant selected “A” as the most important attribute and “B” as the least important attribute; attribute “F” was not selected. I originally left the scenario omitted variables blank (e.g., in scenario #1 I left variable C, D, and E columns empty) however my conditional logit model came back with no observations able to be run due to each observation was missing data. The current setup does not seem correct to me, which is not surprising seeing as how I am having collinearity issues.
Dataset: With each scenario including 3 attributes, a total of 6 outcomes are possible; this is why I have 6 rows for each choice scenario. A "1" implies best while a "-1" implies worst.
Choice A B C D E F
0 1 -1 0 0 0 0
0 1 0 0 0 -1 0
0 -1 1 0 0 0 0
1 0 1 0 0 -1 0
0 -1 0 0 0 1 0
0 0 -1 0 0 1 0
I have searched extensively about this topic and have not had any luck. Any and all help and advice would be greatly appreciated. Thank you in advance.
-Mike