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

[Nils Wlömert <nils.wloemert@gmx.net>]

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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