This article describes how to design experiments for choice-based conjoint analysis (also known as choice modeling).
- A list of brand attributes and levels for each attribute.
1. Select Anything > Advanced Analysis > Choice Modeling > Experimental Design.
2. From the inputs on the right. select an Algorithm for creating the design. The default is Balanced overlap which generates a design where there is a high level of balance for each respondent.
3. Enter the number of Questions per respondent.
4. Enter the number of different design Versions that you want to generate.
5. Only check the Alternative are labeled by first attribute checkbox if your the first attribute in your list is an alternative label.
6. Enter the number of Alternatives per question (excluding None(s)) that respondents will be show.
7. Enter the number of None alternatives.
8. For Attributes and levels, select one of the following options
- Enter in spreadsheet - enter the attributes and levels through a spreadsheet-style data editor with one attribute per column followed by each attribute level by clicking the Add attributes and levels button.
- Enter attributes individually - enter each attribute name followed by a list of levels, delimited by commas.
- Enter number of levels per attribute - A comma delimited list of levels per attribute.
9. For Efficient and Partial profiles designs that use the Attributes and levels spreadsheet option, you can additionally add mean and/or standard deviation priors to optimize your design by placing a column called mean or sd adjacent to each attribute you wish to apply a prior to. Best practice is to do this with all attributes. Priors are designed to reflect the utilities of the survey respondents whereby a high utility for an attribute level indicates a stronger preference and vice versa. The first utility should be 0. The range should be between -3 and 3 relative to the first utility based on your industry knowledge and judgment.
10. Check the Enter prohibited alternatives checkbox if there are combinations of attribute levels that you want to prohibit from appearing in the same choice option. Note that the alternatives that you want to prohibit from appearing together must be on the same row with the attribute levels in the same column as entered in the original attributes and levels spreadsheet.
11. Enter the expected sample size for the experiment. The default is 300, however a warning may be generated, similar to the one below, recommending you increase the sample size if the standard error for any of the attribute levels is greater than 0.05.
12. Click the Calculate button to generate the choice model experiment design.