choice-metrics.com

1. Yes certainly, that is up to you. The most common is that you create overlap across all attributes, but this is not necessary.

2. Mixing informative priors and uninformative priors is usually not ideal because the choice probabilities affect the efficiency and your uninformative priors would not ...

1. In a pilot study you will often find that coefficients are not statistically significant because the sample size may be too low. 100 respondents is a reasonable size for a pilot study though, so often you would see more parameters that are significant. In your case, only 1 parameter is ...

1. Yes. With Treatment A and B, there is no reason why Treatment A would be more/less preferred than Treatment B if the attribute levels are the same. So that means that the constant for such generic alternatives should be the same (so either both 0 or both b0). Note that when using data from a ...

Including an ASC or including a dummy variable that represents the label of the alternative is the same thing. Perhaps that is what the authors did in that paper, not sure. Otherwise, ASCs should always be added during model estimation.

Your ASC expresses the preference between choosing and not ...

You indeed need an ASC for an opt-out alternative. An opt-out alternative is a different type of alternative and hence requires a constant. So your data in long format (used by Nlogit and some other software packages) looks good.

You would immediately know if you overspecify the model or introduce ...

Yes that is correct.

1. Yes, this is correct, but you should remove the asterisk (*) because an opt-out alternative is a different type of attribute. So you need: ;alts = alt1*, alt2*, alt3
2. If alt1 and alt2 are generic, then you would typically use b0 for both alt1 and alt2.
3. Yes, this is correct. If it is not ...

Together with colleagues I have been working on a new blocking algorithm that we aim to submit for publication in the Journal of Choice Modelling later this year. I now have a version working in Excel (using Solver to do the optimisation) and it seems to do a better job in achieving attribute level ...

Correct. Swapping choice tasks across blocks does not affect any design properties, so you can safely do this. The efficiency of the design remains exactly the same.

There is no recommended way of doing this, indeed just a bit of trial and error.

Michiel

Interesting, thank you for letting us know.
I did notice that Ngene sometimes does not accept the candidate set if the row numbers are not consecutive, so that could perhaps have been the issue.

Based on your feedback, we will implement some checks on the candidate set and also consider what you ...