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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