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Table 2 Tests and Fit Statistics (see the table in: Predicting length of stay from an electronic patient record system: a primary total knee replacement example)

From: Statistical models for analyzing count data: predictors of length of stay among HIV patients in Portugal using a multilevel model

PRM   BIC = 445,377.671 AIC = 445,042.083 Prefer Over Evidence
vs NBRM BIC = 198,352.015
AIC = 198,008.241
LRa
dif = 247,025.656
dif = 247,033.841
prob. = 0.000
NBRM
NBRM
NBRM
PRM
PRM
PRM
Very strong
p = 0.000
vs ZIP BIC = 432,948.578
AIC = 432,277.401
Vuongb
dif = 12,429.093
dif = 12,764.682
prob. = 0.000
ZIP
ZIP
ZIP
PRM
PRM
PRM
Very strong
p = 0.000
vs ZINB BIC = 198,103.519
AIC = 197,424.156
dif = 247,274.153
dif = 247,617.927
ZINB
ZINB
PRM
PRM
Very strong
NBRM   BIC = 198,352.015 AIC = 198,008.241 Prefer Over Evidence
vs ZIP BIC = 432,948.578
AIC = 432,277.401
dif = −2.346e+ 05
dif = − 2.343e+ 05
NBRM
NBRM
ZIP
ZIP
Very strong
vs ZINB BIC = 198,103.519
AIC = 197,424.156
Vuongb
dif = 248.497
dif = 584.085
prob. = 0.000
ZINB
ZINB
ZINB
NBRM
NBRM
NBRM
Very strong
p = 0.000
ZIP   BIC = 432,948.578 AIC = 432,277.401 Prefer Over Evidence
vs ZINB BIC = 198,103.519
AIC = 197,424.156
LRa
dif = 234,845.060
dif = 234,853.245
prob. = 0.000
ZINB
ZINB
ZINB
ZIP
ZIP
ZIP
Very strong
p = 0.000
  1. PRM Poisson Regression Model, NBRM Negative Binomial Regression Model, ZIP Zero-inflated Poisson, ZINB Zero-inflated Negative Binomial
  2. a Verified with a likelihood ratio test
  3. b Verified with the Vuong test