Optimal designs for conjoint experiments

Roselinde Kessels*, Peter Goos, Martina Vandebroek

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


In conjoint experiments, each respondent receives a set of profiles to rate. Sometimes, the profiles are expensive prototypes that respondents have to test before rating them. Designing these experiments involves determining how many and which profiles each respondent has to rate and how many respondents are needed. To that end, the set of profiles offered to a respondent is treated as a separate block in the design and a random respondent effect is used in the model because profile ratings from the same respondent are correlated. Optimal conjoint designs are then obtained by means of an adapted version of an algorithm for finding D-optimal split-plot designs. A key feature of the design construction algorithm is that it returns the optimal number of respondents and the optimal number of profiles each respondent has to evaluate for a given number of profiles. The properties of the optimal designs are described in detail and some practical recommendations are given.
Original languageEnglish
Pages (from-to)2369-2387
Number of pages19
JournalComputational Statistics & Data Analysis
Issue number5
Publication statusPublished - 20 Jan 2008
Externally publishedYes


  • conjoint experiments
  • D-optimality
  • optimal block design
  • optimal block sizes
  • prototype testing

Cite this