This topic has been discussed in length in this forum and the conclusion is that there is no easy so solution to find null RLH for ACBC due to the different amount of tasks on respondent level.
Currently I take the effort to actually do exactly that in order to be able to interpet the average RLH - and to do so it needs null RLH as a reference. I'm writing a script (sort of) that calculates null RLH values for every respondent based on data captured in the .CHO file. The idea is then to average those null RLH values (arithmetic) so that I can compare the "average null RLH of the model" with the actual average RLH of the model.
Does that make sense?
Also, if my calculation of the "average null RLH of the model" is correct, the figure should be very similar to the average RLH from a study with let's say n = 200 robotic respondents, correct? At least that's what I'd expect from a rational point of view.