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
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
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.