In the standard CBC module we have the luxury of having a lower RLH estimate produced during the estimation that allows us to Identify respondents who are (likely to be) answering tasks at random. I understand the derivation of this lower RLH stat is extremely difficult in ACBC/HB studies due to the fact that many respondents see different combinations of choice sets and tradeoffs (based on how they answer the various sections of the ACBC). This being the case is there a substitute measure we can use that might highlight respondents answering at random - other than looking at things like speeding / straightlining etc.
Is running a monotone regression and using the Tau statistic of any use? I'm guessing no for the same reason as RLH, but I'm looking for a way to eliminate troublesome respondents which we all know exist on panels.