Re: st: effects-type coding of attributes in discrete choice modeling

[Shehzad Ali <drshehzad_ali@yahoo.com>]

Check xi3 and look for deviation coding.
Shehzad

On Fri, 26 Nov 2010 04:16 Etc/GMT+12 Nils Wlömert wrote:

>Hello everyone,
>
>I am new to this list and fairly new to Stata, so I hope my question is not trivial or has been answered before. I searched the FAQs and the mailing list archives and I could not find anything about this specific question regarding choice-based conjoint, resp. discrete choice models.
>
>I would like to analyze data from a choice-based conjoint survey incl. 6 attributes + a base alternative (no-choice option):
>Attribute 1 & 2   (5 levels each) representing alternative specific price attributes
>Attribute 3 - 6   (4 levels each) representing different product characteristics
>+ the no-choice option
>
>The data set:
>There are 8 observed choices for each respondent. Each choice is between 3 alternative configurations of the product and the no-choice option, i.e., there are 32 lines for each respondent in the data set representing one alternative each (N=2540). The dependent variable (choice) is indicated by a 1,0 dummy variable in an extra column. There is currently one column for each attribute indicating the level of the attribute for the specific alternative (values 1-5 for the price attributes and values 1-4 for the product characteristics) and one column for the no-choice option (values 1 or 0). There are also columns indicating the respondent ID and the choice set ID.
>
>The analysis:
>I have so far computed part-worths for each attribute using mlogit with linear (or numeric) coding of all attributes - choice being the dependent variable and the 6 attributes + no-choice option the independent variables. However, I would like to compute part-worths for every level of the product attributes (i.e., attributes 3 - 6 with levels 1, 2, 3, 4) using effects-type (or nominal) coding. Any help on how I could achieve this will be much appreciated!
>
>I would then like to compare alternative modeling approaches for the no-choice option with regard to the relative fit of the model (e.g., as a dummy variable in multinomial logit versus nested in a separate nest using nlogit). Also, I would like to compare different coding of the linear price attributes (e.g., 1,2,3,4,5 vs. mean centered -1, -0.5, 0, 0.5, 1). So any help on how to assign different values to attribute levels would also be much appreciated!
>
>Thank you!
>
>Nils.
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