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Table 1 Summary statistics relating to growth curve models fit to the control data

From: Different ODE models of tumor growth can deliver similar results

model

− 2*LL

AIC

w(AIC)

AICc

w(AICc)

BIC

w(BIC)

generalized logistic

5159.69

5179.69

.0037

5180.07

.0038

5190.13

.0038

Gompertz

5182.79

5198.79

2.66E-07

5199.01

2.88E-07

5207.15

7.72E-07

von

Bertalanffy

5189.97

5209.97

9.94E-10

5210.35

9.95E-10

5226.42

5.05E-11

Simeoni

5148.52

5168.52

.9963

5168.90

.9963

5179.01

.9962

  1. Notes
  2. LL log likelihood, AIC Akaike information criterion, w(AIC) weights derived from candidate model AIC values, AICc corrected Akaike information criterion, w(AICc) weights derived from candidate model AICc values, BIC Bayesian information criteron, w(BIC) weights derived from candidate model BIC values
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BMC Cancer

ISSN: 1471-2407

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