I set up a survey where respondents had to answer 8 best-worst questions. In each question, 4 attributes were shown.

The initial sample size was around 1800.

But 800 were disqualified (speeders, etc.), resulting in a final sample size of 1001 respondents.

I ran logit analysis and got the following results:

Log-likelihood for this model -25518,11507

Log-likelihood for null model -28998,85231

Difference 3480,73724

Percent Certainty 12,00302

Akaike Info Criterion 38633,44920

Consistent Akaike Info Criterion 38694,21861

Bayesian Information Criterion 38687,21861

Adjusted Bayesian Info Criterion 38664,97311

Chi-Square 5786,33177

Relative Chi-Square 826,61882

The p-value is 0.003448, significant at p < 0.01-

The percent certainty seems very low.

I rad in the forum that that percent certainty is the equivalent of Mcfadden's rho-squared (pseudo R²) and I know that a low R² in social and behavioral sciences is not a problem.

But in this case, I have no idea and I didn't find any percent certainty benchmark.

So, I would like to ask your opinion about it.

Is the percent certainty good enough?

What should I do to increase it?

Thank you very much in advance.

Bests regards.

MIkael

Thank you very much.

Have a nice weekend.

Kind regards,

Mikael