Design Choice-based Conjoint (CBC) study in Python/ R

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We need a Choice-based Conjoint study developed in order to survey customers about features of a product. This is a proof of concept that will be iterated so ongoing work should be expected. The study should be kept flexible to allow future enhancement.

We're quite clear on the design, attributes/ levels (4/ 4) of the study and already have an exact working prototype using an online choice-modelling survey platform.

The developer will also need to create the front-end of the application where the respondent will go through the pair-wise conjoint. The pair-wise options will be images instead of textual descriptions of the attributes/ levels. We already have the images prepared and know how they will match to combinations of levels for which an algorithm will be required to query the right image.

If you are interested, you will:

- Already have prior experience in using statistical programming language such as python/ r

- Previously developed conjoint studies and able to quickly refer to existing libraries/ packages to develop the study

- Quite familiar with the mathematics behind choice modelling and able to suggest different conjoint designs such as adaptive (ACBC) max diff, ranking, pair-wise, etc.

- Available to work immediately or soon on the project.

Skills: Data Science, Python, R Programming Language, Statistical Analysis

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About the Employer:
( 1 review ) Brisbane, Australia

Project ID: #17393686

10 freelancers are bidding on average $590 for this job


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