New Technical Paper: Consistency Cutoffs to Identify "Bad" Respondents in CBC, ACBC, and MaxDiff

Last updated: 29 May 2020

Over the last few years, the incidence of bad respondents is increasing. Conjoint analysis and MaxDiff have a fit statistic called RLH when using HB estimation that helps identify bad respondents. As long as the conjoint or MaxDiff questionnaire has enough questions relative to the number of levels or items in the study, random responders can be identified with a high degree of accuracy. This paper, authored by Bryan Orme of Sawtooth Software, gives instructions for generating random data to identify the RLH cutoff that has a high probability of identifying random respondents. It is available in the middle of the General Conjoint section of the website's Technical Papers library.

Read the paper: Consistency Cutoffs to Identify "Bad" Respondents in CBC, ACBC, and MaxDiff