Hi everybody,

I'm using brms package in R for logistic regression. I compared two models using the 'looic' command. The output contains the following information:

Output of model 'SA1nest.brm1':

Computed from 4000 by 91 log-likelihood matrix

Estimate SE

elpd_loo -54.9 8.4

p_loo 15.3 3.7

looic 109.9 16.7

------

Monte Carlo SE of elpd_loo is NA.

Pareto k diagnostic values:

Count Pct. Min. n_eff

(-Inf, 0.5] (good) 86 94.5% 920

(0.5, 0.7] (ok) 4 4.4% 221

(0.7, 1] (bad) 0 0.0%

(1, Inf) (very bad) 1 1.1% 12

See help('pareto-k-diagnostic') for details.

Output of model 'SA1nest.brm2':

Computed from 4000 by 91 log-likelihood matrix

Estimate SE

elpd_loo -48.3 5.8

p_loo 6.5 1.3

looic 96.6 11.7

------

Monte Carlo SE of elpd_loo is 0.1.

All Pareto k estimates are good (k < 0.5).

See help('pareto-k-diagnostic') for details.

Model comparisons:

elpd_diff se_diff

SA1nest.brm2 0.0 0.0

SA1nest.brm1 -6.7 4.2

............................................

Now I understand that the model with the least looic value is the best. I just wanted to know what the negative value implies under the Model comparisons. Somebody please elaborate.

Thanks