Two alternatives in choice experiment

[#1]

Hi, I am designing an experiment with two discrete choice options, 2 factors each with 2 levels, and 1 with 6 levels. I have tried DOE consumer studies, choice design but unable to make this work. Any help will be greatly appreciated. Thanks.  

[#2]

Hi @aus22,

Welcome in the Community !

May I ask the context of your study ? Is it linked to consumer choice experiments ?

There are multiple ways to create a DoE with 3 discrete choice factors, using Choice Designs or Custom Designs platform, depending on your objectives and context.

• The basic concept behind Choice design is to "pick a winner" between different profiles (factors treatments) used in several choice sets for different respondents. Analyzing the several selected options picked in different choice sets enable to evaluate the relative importance and significance of the attributes (factors) tested, and find the best level combinations in terms of utility score across all respondant responses. You can find an example here : Run the Choice Design and Analyze the Results (jmp.com) There may be more parameters to consider when using choice design, such as number of attributes that can change within a choice set, number of profiles per choice set, number of choice sets per survey, number of surveys and number of respondents per survey. 
• The Custom design is a more general (and versatile) platform, to identify significant terms and best levels based on an assumed model. It may however not be suitable for analyzing consumer/survey responses, the use of CHoice design may be more useful.

Depending on your objectives and needs, one platform may be more suitable than the other. Could you describe the context, objectives and needs of your experimental design ? If related to consumer choices, how many respondents and surveys are you expecting ?

I attached two designs as an example, one created with the choice design platform with basic settings and your factors descriptions, and another one created with the Custom Design platform. You can also read the documentation and look at the examples in the JMP Help section : Example of a Choice Design 

Hope this first response will help you,

[#3]

Hi Victor, thank you for the help. The objective is to assess which one of the set of restaurant attributes are more important for consumers. We have three attributes in this study as I pointed out. I am trying to create a design that provides respondents two options (alternatives) to pick from, these will not be labelled. Each will have different levels of those attribute levels. Hope this clarifies the study? Could you help further please? I do see the design you shared and the Choice design seems to be the more appropriate one. In that design does the survey column provides the repeated runs for each respondent? Also could you also tell me how can I put constraints on one of the attributes to not vary? Thank you again. 

[#4]

Also, how do I add 2 alternatives to the choice design, the kind you shared? Thanks again. 

[#5]

Hi @aus22,

Ok thanks, the context is now clearer and you may need effectively a Choice Design.

In order to set up your design, you have several parameters to define in the Design Generation panel : 

• The "Number of attributes that can change within a choice set" is the number of factors that you can vary the levels between experiments (called "profiles") in the choice set. In my design, only 2 of the 3 factors vary between the 2 experiments in the same choice set (example for survey 1, choice set 1, X1 and X2 vary, but not X3 (fixed at L1)). This should answer your last question ?
• The "Number of profiles per choice set" is the number of experiments in the same choice set that the respondent will have to choose from. In my example, I let this value to 2, but you can augment it if you would like to reduce the number of choice sets/surveys for example.
• The "Number of choice sets per survey" : collection of profiles.
• The "Number of surveys" : collection of choice sets.
• The "Number of respondents per survey" : if you have several respondents, change the value to the number of people answering each survey, so that each respondent has its own column for the values. It will be automatically taken into account in the script "Choice" for the analysis, filling the "Subject ID" role with the "Respondent" value.

More infos on terminology here : Choice Design Terminology

Hope this response clarify the design and terminology ?

[#6]

Hi Victor thanks a lot this is most helpful. A follow up question please. How can I select the attribute that does not change? Thank you. 

[#7]

Hi @aus22,

The attribute that does not change will be randomly selected for each choice set, so that every attribute has the same probability of staying fixed or changing for each choice set. I don't know a way to predefine the attribute that won't change in a specific choice set ?

I hope I did undertsand your question ?

[#8]

Got it thank you Victor most kind!!

[#9]

Hello Victor, I was able to generate a study design, see enclosed. Table 1 is what the software gave me. I replaced the choice set column with the product alternatives that I wish to offer in the choice sets - thats Table 2. Am I interpreting this correctly? Also, am I able to use this design to simulate data and estimate my utility functions? You will see the last two columns of Table 1 related to that trial. Thank you indeed. 

[#10]

Hi @aus22,

Please add your JMP file instead of Excel file, as all scripts are lost when using Excel files (unless converting files from JMP to Excel with the Table Attributes Add-In).

Table 2 seems to be a transpose of Table 1, or did I miss something ? In any case yes, table 2 is a comparative file between products in column, separated in 3 choice sets with 4 products in each choice set.

Yes you can simulate data when creating your design, go into the red triangle next to "Choice Design" and click on "Simulate Responses" : 

It will create formula columns for probability calculations and choice simulated, depending on the marginal utility values entered : 

You can then launch the script "Choice" (or go to Analyze, Consumer Research, Choice) and analyze the simulated Choice response. You will have access to various Profilers (utility, probability profiler) and comparison analysis, as well as Willingness to Pay metric if you have specified your variable Price as Continuous numerical factor type.

You can practice with the dataset "Laptop Results.jmp", available in the Sample Index (Help, Sample Index) and follow the analysis method on this use case here : Example of Making Design Decisions

Hope this answer will help you,