Conjoint Module

A lightweight, embeddable conjoint analysis module for survey research.

Conjoint analysis (considered jointly) presents respondents with structured choice tasks — profiles varying across pre-defined attributes and levels — and recovers part-worth utilities via discrete-choice modelling. This module is designed to be embedded as a block inside an existing survey platform via a shared participant key; data are exported in R-ready format.

Optionally, generative AI can be used to (1) suggest attributes and levels from a free-text study description, (2) render alternatives as coherent natural-language vignettes, or (3) generate scenario images — all intended to improve scenario evocation and reduce satisficing in participants.

D-optimal designs are generated via coordinate exchange on an effects-coded information matrix, initialised from a level-balanced random start.

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Created by Philipp Brauner.