nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

Choice platform, "None of these options" alternative - how to handle?

n_ryazantsev

Hello, I use Choice Platform for Discrete Choice experiments and meet difficulties to implement "None of these options". Anyone knows how to handle it?

For example, I run simple case with only two attributes - brand and price.

- I add one more choice alternative "None of these options" in profiles table .

- Since nor price or brand is relevant to this option, I assign "None" level for the brand and price attributes for this choice.

- Respectively, "None" attribute has level "0" for all normal choices and "1" for "None" choice.

The issue is that in such setup JMP gives me calculation error. All utilities become zeros and errors become huge. If I replace "None" price with some other values from the levels what I have for normal choices, it works... but it's incorrect since the "None" option impact utility for given price level.

This is strange because "None of these options" is a must in DC experiments. So pity that JMP guides don't cover this topic.

So, what to do?

Accepted answers

n_ryazantsev

Melinda answered me by e-mail, so I post solution here.

The idea is to re-code nominal variables as binary dummy variables, set their type as ordinal and conduct analysis by them, not by original nominal variables. One of level within each attribute should be leaved out as reference baseline with utility level=0.

"No choice" should be coded similarly - as 0 for all normal choices and as 1 for "no choice" choice.

As result, it becomes possible to calculate utility for "no choice" with zero baseline.

It works great, thank you, Melinda! Moreover, as an aside, it becomes possible to measure likelihood ratio test significance for each level, not for all levels combined, this is very useful. The only drawback is a bit more work to construct a model (more clicks), especially for interactions.

I added screenshot to illustrate changes in standard sample to accommodate "No choice" option. 9202_2015-07-13 10_58_41-Choice Model - JMP Pro.png

melinda_thielba

And I've attached are a couple of sample data tables that you can use to try it at home!

Thanks for posting the information for us. I like your idea of giving the "no choice" option a price, indicating that you think the consumer would be buying another brand with a lower price. How you choose to code the attributes of the "none" is up to you--just be careful when you interpret the results.

For others who are interested in this topic: Using an indicator variable for the "none" response can cause bias in your parameter estimates. This paper discusses an alternative model for the No Choice option using a nested multinomial logit instead of an indicator variable.

Vermeulen, B., Goos, P., & Vandebroek, M. (2008). Models and optimal designs for conjoint choice experiments including a no-choice option. International Journal of Research in Marketing, 25(2), 94–103. doi:10.1016/j.ijresmar.2007.12.004

I'm currently working on some comparisons between the indicator and the nested logit. If others are working on this problem, I'd love to hear from you.

Thanks!

Melinda

Pizza Profiles.jmp

Pizza Responses With No Choice.jmp

All comments

melinda_thielba

You can use a No Choice in JMP 12, though it takes a little work with the data table, and the best way to do it depends on you data and how you normally model the No Choice option (there are different schools of thought on that). I'm happy to work with you. You can message me through the forum or e-mail me directly for more information.

In JMP 13, we will be including an option to model "no choice" explicitly, and I'd love to talk with you about how you use this feature and the best way to report results from it.

Thank you!

Melinda Thielbar

JMP Research Statistician Developer

Melinda.Thielbar@jmp.com

n_ryazantsev

Hello, Melinda, thank you for your answer, love to see it here

I use separate tables for choice profiles and for actual choice run.

Within this setup, I can use either unique id for every choice or use grouping by choice set with sequential number of choice. It works both.

So far I have to totally delete "None" options and treat all answered choice sets with chosen "None" option as unanswered.

This is generally OK and gives more or less good information about utilities for real alternatives.

However, I would like to see the total utility for "None".

The logic behind this would be treating the "None" as "Other", so utility for "None" should represent preference for all other alternatives that was not shown in experiment. As soon as I know, this approach is the most common.

I'll cc you by e-mail but I think your explanations would be fruitful for the community.

n_ryazantsev

Melinda answered me by e-mail, so I post solution here.

"No choice" should be coded similarly - as 0 for all normal choices and as 1 for "no choice" choice.

As result, it becomes possible to calculate utility for "no choice" with zero baseline.

I added screenshot to illustrate changes in standard sample to accommodate "No choice" option. 9202_2015-07-13 10_58_41-Choice Model - JMP Pro.png

melinda_thielba

And I've attached are a couple of sample data tables that you can use to try it at home!

I'm currently working on some comparisons between the indicator and the nested logit. If others are working on this problem, I'd love to hear from you.

Thanks!

Melinda

Pizza Profiles.jmp

Pizza Responses With No Choice.jmp