I was wondering if there is a minimum sample size for conducting discrete choice experiment. From what I know, if choosing the number of sample size is a problem, one can resort to using the magic number of 400+. Although it would be nice to have such sample size, but then this kind of experiment is expensive, so 400+ or more may be impractical. I have read several journal articles about DCE and I was surprised that their sample sizes did not even reached 400.
According to Orme (2010), one rule of thumb for an acceptable sample size is:
$$ n \geq 500c/ta, $$ where:
nis the number of respondents,
tis the number of is the number of tasks,
ais number of alternatives per task (not including the none alternative),
cis the number of analysis cells. When considering main effects,
cis equal to the largest number of levels for any one attribute. If you are also considering all two-way interactions,
cis equal to the largest product of levels of any two attributes.
For example, if you are only considering main effects in a 3×3×4 design with three alternatives (plus one for 'choose none') and twelve choice tasks per respondent (without placing respondents into different blocks), you will need at least:
$$ n \geq 500×4/(12×3)\approx56 $$ respondents.
Online conjoint analysis tools will, such as Conjoint.ly, will be able to calculate this automatically when you set up an experiment.