Multinomial logit on MaxDiff data is equivalent to a single-class latent class analysis.
The table below shows the output of multinomial logit using MaxDiff data on technology companies. The distribution of respondent parameters is displayed for each alternative, with blue and red columns corresponding to positive and negative parameters respectively:
Requirements
- A document containing your MaxDiff respondent data.
- The MaxDiff experimental design.
Please note these steps require a Displayr license.
Method
- From the toolbar, go to Anything > Advanced Analysis > MaxDiff > Multinomial Logit.
- Select your experimental design. You can use an existing table, an R output, variables from a data set, or a URL. For this example, I'm using an existing table that I've added to my project by selecting Table > Paste or Enter Table. Then add data by clicking on the red Paste or type data button in the object inspector.
The Design input table needs to be in a form similar to the one shown below. The 'Version' column is optional when there is only one version in the design. The 'Question' column is also optional. However, if these columns are included, they must have the names 'Version' and 'Question'. The columns after this contain the indices of the alternatives presented to the respondents.
- Select the Version variable from your respondent data set. If you only have one version, then this can be left blank.
- In Best selections, choose the variables in your data set that identify the options that were selected as best, or most preferred, for each task. The order of the variables selected should match the order from the design (i.e., the variable for the first task should be selected first, the variable from the second task should be selected next, and so on).
- In Worst selections, choose the variables in your data set which identify the options that were selected as worst, or least preferred, in each task.
- OPTIONAL: Click on Add alternative labels, and enter the alternative names in the first column of the spreadsheet editor. The order of the alternatives should match the order in the design.
- Click the Calculate button if the model doesn't automatically run.
- OPTIONAL: In the Save Variable(s) section, choose the variables you want to save. You can read more about each option in the "Next" section below.
- OPTIONAL: In the Diagnostics section, choose the diagnostics of your choice.
Next
How to Do Latent Class Analysis
How to Use Hierarchical Bayes for MaxDiff
How to Create MaxDiff Model Ensembles
How to Create a MaxDiff Model Comparison Table
How to Create a MaxDiff Experimental Design
How to Save Respondent-Level Preference Shares from a MaxDiff Latent Class Analysis
How to Convert Alchemer MaxDiff Data for Analysis in Displayr
MaxDiff - Individual-Level Coefficients
MaxDiff - Proportion of Correct Predictions
MaxDiff - RLH (Root Likelihood)
MaxDiff - Sawtooth-Style Preference Shares (K Alternatives)