I've received survey data from a sample of 1000 responses from a choice-based conjoint analysis where a respondent were presented with two cards and had to choose their preferred option. In the survey there were 3 attributes with 4 levels each and the sample was split in to 5 blocks with 10 choice sets presented to each respondent. Each of these blocks had 200 responses in them.
The design of the conjoint choice-sets was not done by me, but I'm now stuck with analysing these results. I've primarily used SPSS before, but from my quick research it seems SPSS might not be suitable and thus I might have to resort to R. I have no experience of doing Conjoint analysis on a split-sample so I'm rather desperate to find help with this.
Are there any examples of R or SPSS used out there of analysis of a choice based conjoint for a split sample?
For reference, a similar question was asked in this thread
EDIT: I was able to put together a model using the mlogit-package and my model output is the following:
Call: mlogit(formula = choice ~ speed + price + cat1 + cat2 + cat3, data = test.data, method = "nr", print.level = 0) Frequencies of alternatives: 1 2 0.71558 0.28442 nr method 5 iterations, 0h:0m:0s g'(-H)^-1g = 0.000741 successive function values within tolerance limits Coefficients : Estimate Std. Error t-value Pr(>|t|) 2:(intercept) -0.3582505 0.0372617 -9.6144 < 2e-16 *** speed -0.1726341 0.0105252 -16.4020 < 2e-16 *** price -0.1672694 0.0073242 -22.8380 < 2e-16 *** cat1 0.0965562 0.0415806 2.3221 0.02023 * cat2 0.8722452 0.0526031 16.5816 < 2e-16 *** cat3 -0.0788710 0.0451093 -1.7484 0.08039 . --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Log-Likelihood: -5419.7 McFadden R^2: 0.093196 Likelihood ratio test : chisq = 1114 (p.value = < 2.22e-16
Speed & Price are numerical variables while cat1, cat2 & cat3 are dummy categorical variables and cat4 is the reference category that is left out from the model to avoid singularity.
I have previously used the Conjoint package which has a function (caImportance) for constructing relative factor importance and function (caUtilities) which calculates utilities of attribute levels. Is it possible for me to get similar outputs from my model that was constructed using the mlogit package?