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I am assuming that you are computing the WTP as a ratio of two coefficients, i.e. that you are considering two continuous attributes (of which one is price or cost) that are not dummy coded, i.e. WTP = b1 / b2.

The variance (and hence standard error) of WTP can then be computed using the Delta ...

Greetings everyone,
I have successfully calculated the WTP in Nlogit, but how could I calculate the WTP Standard Errors and 95% Confidence Intervals for each WTP?
Thanks in advance,
Best regards,
Lohas

1. OOD designs do not care about the attribute levels, the design will be the same.
2. Ngene can handle any number of attributes, it is up to the analyst to determine the number of relevant attributes.

Michiel

Dear Michiel,

Really appreciate for your time and help! It helped me a lot on the CE ...

1) All looks fine. The design will not change when you add the no choice (alt3) alternative, but the D-error will change, so it is good practice to add the no choice alternative with a constant, i.e. U(alt3) = b0. I notice that you use levels 1,2,3 except for F. It is highly unusual to use such ...

1. Yes
2. The range should be as wide as possible while keeping it realistic.
3. Then your WTP measure will also not be statistically significant (i.e., have a very large standard error).
4. It is difficult to design data specifically for models other than MNL, so it is common to design the data ...

1. It will work but there may be several weakly dominant alternatives because of your price attribute. This cannot be avoided with an orthogonal design.

2. That is a model estimation question, not an experimental design question. Most people estimate first an MNL, and then an RPL panel or latent ...

1. Yes that could happen with inappropriate or non-informative (zero) priors. If your priors reflect the fact that price is a dominant attribute then this situation will automatically be avoided with appropriate priors since a choice task where one alternative is chosen by, say, 99% of the people ...

1. Yes
2. The range should be as wide as possible while keeping it realistic.
3. Then your WTP measure will also not be statistically significant (i.e., have a very large standard error).
4. It is difficult to design data specifically for models other than MNL, so it is common to design the data ...

1. I think that is fine.
2. If you think that behaviour in different cities is more or less the same, then you can just do a pilot study in a single city and use those priors for all cities. Preferably your pilot study covers respondents from all cities.

Michiel

Dear Michiel,

Many thanks!

1 ...

1. That depends on your research question. But I think that asking vegetarians about beef consumption does not make sense.
2. No, in a stated choice experiment you can task for new alternatives that may not yet exist or have been considered. For example, if the price of purchasing beef online is ...