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Latent Class joint Utility

Hello,

I wanted to ask the best mathematical equation to generate a single utility algorithm after generating Latent Class utilities, As from Latent Class we get the utilities for each group separately.

So if we assumed 2 groups, group 1 with 40% segment share & group 2 with a 60% segment share then will the joint utility for every level be as follows:
(Ugp1*0.4)+(Ugp2*0.6)

also, I wanted to ask about the importance/use/significance of the average maximum membership probability reported towards the end of the estimation results report.

Regards'
asked May 8, 2020 by AMYN Bronze (3,000 points)

1 Answer

+1 vote
 
Best answer
From the documentation, I'm seeing that it is a simple weighted average of the group utilities and the weights being the probability of group membership (https://www.sawtoothsoftware.com/help/lighthouse-studio/manual/index.html?hid_smrt_useslatent.html).

However, generally we would recommend to use HB to produce individual-level utilities.  This allows respondents to be unique, rather than be constrained to a weighted average of the groups.

I think the main use of average probability membership is one part of evaluating cluster solutions if you are trying to pick between, say, a 3 group versus a 4 group solution.  Higher probability on average would indicate a "stronger" cluster solution, and would be used alongside other things like how many people are in each cluster, etc. to help you choose with N-group solution to move forward with.
answered May 8, 2020 by Brian McEwan Platinum Sawtooth Software, Inc. (52,630 points)
selected May 9, 2020 by AMYN
Thank you very much Brian for your reply and explanation. Indeed I will use HB to generate the individual utilities along the way it is just that I need to compare the results from both methods when I present my research.
Have a good day.
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