choice-metrics.com

Ok great!

For others interested in the answer:

The sample size calculation in our paper is based on the standard error for a single respondent. The standard error from the pilot study therefore needs to be normalised by the number of respondents in the pilot study, so use se/sqrt(samplesize ...

There are a few things happening.

First, to create the candidate set, Ngene randomly generates choice tasks and evaluates each choice task against your reject and require constraints. The require constraints are very strict and despite Ngene rapidly evaluating millions of choice tasks, Ngene does ...

If you hover the mouse over the zero point in the search graph, you can see that the design actually has an Undefined D-error, which means Infinite. Since we cannot plot Infinite on the graph, it is plotted as zero, but it is actually not zero. If you click on it, you can see that the covariance ...

Yes, absolutely, you can use zero priors.

In the candidate set, you may also want to make sure that you avoid any dominant alternatives, e.g. an alternative with a lower toll, lower mean, and lower stdev. Similarly, you may also want to remove any stochastically dominant alternatives, e.g. (4,6,8,8 ...

We first designed the distributions, for example: (4,4,10,12,12).

Then we calculated (in Excel) the mean and stdev for each distribution. In the example distribution above:
mean(4,4,10,12,12) = 8.4
sddev(4,4,10,12,12) = 4.1

We calculated this for all distributions and created a candidate set with ...

1. With 40 rows and 7 cost levels, with perfect attribute level balance each level would appear 40/7 = 5.7 times on average within the design. So it is probably better to use 4-8 (values around 6) rather than 2-6.

2. A script should properly specify the model as you would most likely estimate it ...

By minimising the D-error, Ngene is optimising the trade-offs across all attributes simultaneously. Therefore, it is not necessary to impose non-overlap constraints.

The reason that is happens is because your priors are quite large for some of the attributes. This indicates that some of these ...

Ok yes. So alt1 and alt2 will be more costly, but will have better levels for the other attributes. That makes sense.

Make sure that you run any script using the modified Federov algorithm for quite some time. Since you have 40 rows, and the candidate set by default has 2000 rows, you would need to ...

You need to specify the status quo alternative with the actual attributes and reference levels, and then tell Ngene that all alternatives are unlabelled so that Ngene can automatically avoid dominant alternatives.

Assuming that you are using Ngene version 1.X (desktop/Windows), you need:
;alts ...

A status quo alternative is typically different from an opt-out alternative in that it DOES have attributes and levels. Namely, it has fixed levels of certain attributes. This can be achieved by constraints such as:
;require:
sq.ap = 1, sq.br = 1, ... etc.
;model:
U(sq) = asc_sq + b_ap.dummy * ap ...