Measures of model fit statistics for multiple models.
blr_multi_model_fit_stats(model, ...) # S3 method for default blr_multi_model_fit_stats(model, ...)
| model | An object of class |
|---|---|
| ... | Objects of class |
A tibble.
Other model fit statistics:
blr_model_fit_stats(),
blr_pairs(),
blr_rsq_adj_count(),
blr_rsq_cox_snell(),
blr_rsq_effron(),
blr_rsq_mcfadden_adj(),
blr_rsq_mckelvey_zavoina(),
blr_rsq_nagelkerke(),
blr_test_lr()
model <- glm(honcomp ~ female + read + science, data = hsb2, family = binomial(link = 'logit')) model2 <- glm(honcomp ~ female + read + math, data = hsb2, family = binomial(link = 'logit')) blr_multi_model_fit_stats(model, model2) #> Measures Model 1 Model 2 #> loglik_null Log-Lik Intercept Only -115.644 -115.644 #> loglik_model Log-Lik Full Model -80.118 -75.210 #> m_deviance Deviance 160.236 150.420 #> lr_ratio LR 71.052 80.869 #> lr_pval Prob > LR 0.000 0.000 #> mcfadden MCFadden's R2 0.307 0.350 #> adj_mcfadden McFadden's Adj R2 0.273 0.315 #> m_aic ML (Cox-Snell) R2 168.236 158.420 #> cox_snell Cragg-Uhler(Nagelkerke) R2 0.299 0.333 #> m_bic McKelvey & Zavoina's R2 181.430 171.613 #> mckelvey Efron's R2 0.518 0.523 #> effron Count R2 0.330 0.379 #> nagelkerke Adj Count R2 0.436 0.485 #> count_r2 AIC 0.810 0.830 #> count_adj BIC 0.283 0.358