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Interaction effects in ACBC HB, Estimate Task-Specific Scale Factors, and Graph in ACBC HB

Dear Sawtooth community,

I have 3 questions about HB running with ACBC data.

1. I've runned an HB before without interaction effects and I exported utilities (hbu) and got a file containing individual-level main effects from this HB. Then I used the modified 2-Log Likelihood test using this file to decide if I need to include interactions in the final HB analysis.

Here is the result (I have 5 attributes in the ACBC):
Run                        2LL P-Value for Interaction Effect      Gain in Pct. Cert. over Main Effects
Attribute 1 * Attribute 3       0.00000                            0.36%
Attribute 2 * Attribute 3       0.00000                            0.30%
Attribute 1 * Attribute 2       0.00000                            0.30%
Attribute 2 * Attribute 4       0.00000                            0.20%
Attribute 1 * Attribute 4       0.00000                            0.20%
Attribute 3 * Attribute 4       0.00009                            0.12%
Attribute 2 * Attribute 5       0.00899                            0.09%
Attribute 1 * Attribute 5       0.08226                            0.06%
Attribute 3 * Attribute 5       0.20223                            0.04%
Attribute 4 * Attribute 5       0.22119                            0.04%

All the gains in Pct. Cert over main effects are under 1%. Does this mean I don’t need to include interaction effects in the final HB analysis? I’m just concerned about the negative impacts on the results if I include interaction effects in the final HB running.

2. In the HB settings, do you recommend selecting Estimate Task-Specific Scale Factors (Otter’s method)? And if I select Otter’s method, do I need to active "Save Random Draws" (I just found this from the help file)?

3. In the HB settings, under Graph this section, the "Graph Population Exponential Moving Averages" should be selected, right? Also, is it appropriate to specify the starting seed as 1?

I’m new to HB estimation and thanks in advance!
asked Feb 25 by Xinlei Hu (340 points)

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