Dear Prof. Michiel Bliemer,

I'm working on DCE and conducting research about farmers' selection of insurance using a discrete choice experiment. In my DCE research, I have three alternatives – insurance type1, insurance type2, and “nothing to choose” (opt out). I have 4 attributes, 2 attributes with 3 levels, 1 attribute with 4 levels and 1 attribute with 2 levels.

My orthogonal design for pilot survey was:

Design

;alts = alt1*, alt2*, alt3

;rows = 12

;orth = seq

;block = 3

;model:

U(alt1) = b1 * A[0,1,2] + b2 * B[0,1,2] +b3.effects* C[0,1]+ b4 *D [0,1,2,3] /

U(alt2) = b1 * A[0,1,2] + b2 * B[0,1,2] +b3.effects* C[0,1]+ b4 *D [0,1,2,3] /

U(alt3) = b5

$

I conducted and collected data (total for 3 blocks - 47 respondents) to get prior values for mixed logit design.

I have a few questions if you can help me.

My questions are following:

1) I conducted my pilot survey and I have a problem with coding data for further analysis. I'm not sure if one attribute needs to be coded as one variable, or every level of attribute needs to be coded as one variable? So, I would kindly ask you if you can take a look at the attached link https://drive.google.com/file/d/1sN5MuX ... sp=sharing to see does any of this 2 tables is correct for coding data from choice.

Additionally, how can I code 3rd alternatives if it represents “nothing to choose”, and it is not defined with any attribute?

2) How to get prior values from my orthogonal design to design an efficient mixed logit model? To analyse the results of my pilot study do I need to use a mixed logit command to find the prior values? I don't understand how to proceed to get prior values for mixed logit design.

Thank you in advance!

Best regards,

Tajana