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Calculating standard errors of effects coded part-worths in CBC/Logit

Hello Sawtooth,

for a thesis in the course "market research" at my university I should reproduce the results of the CBC/Logit analysis of a given conjoint study made with SSi-Web. For a deeper understanding of conjoint, my teachers said I should use the statistical software R.

Now my problem: With the effect coding of the data set, I conducted a maximum likelihood estimation with a existing R-function. I have nearly the same results as SSi but, now the problem, just 17 values from 23 attribute levels with 6 attributes (sum(levels) - #attributes). I know how to calculate the missing effects through the effects coding, but I do not understand how I can calculate the standard error of the missing part-worths in the estimation. Can you help me with this, please? Is there a way to calculate the missing standard errors from the estimated ones?
asked Jun 10, 2014 by anonymous

1 Answer

0 votes
The standard errors are calculated as follows:

For part-worth coding, the first n-1 levels are simply the square root of the diagonal value from the estimated variance/covariance matrix.  The omitted level is the square root of the sum of the variances & covariances for that attribute.  For example, assuming a very simple variance/covariance matrix:

a b c 0 0 0
d e f 0 0 0
g h i 0 0 0
0 0 0 j k l
0 0 0 m n o
0 0 0 p q r

For attribute 1 (a 4 level attribute), the omitted level 4's standard error is the square root of the sum of elements a-i.

For linear (continuous) terms, the standard error is similarly the square root of the diagonal value from the matrix.
answered Jun 10, 2014 by Walter Williams Gold Sawtooth Software, Inc. (15,075 points)
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