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Table 2 Goodness of fit for the 1- and 2-state Hidden Markov Models for seven patients

From: Major depressive disorder as a nonlinear dynamic system: bimodality in the frequency distribution of depressive symptoms over time

ID

Model

Θ1

Θ2

Θ2 - Θ1

logl

AIC

BIC

nfree

BC

A

1

4.87

  

−158.89

319.77

322.42

1

.36

 

2

4.87

4.87

0.00

−158.89

327.77

340.99

5

 

B

1

4.94

  

−164.52

331.05

333.69

1

.43

 

2

4.94

4.94

0.00

−164.52

339.03

352.25

5

 

C

1

4.21

  

−210.47

422.93

425.58

1

.53

 

2

3.26

6.81

3.55

−158.53

327.06

340.28

5

 

D

1

5.87

  

−300.57

603.14

605.78

1

.63

 

2

3.02

7.73

4.71

−175.20

360.39

373.62

5

 

E

1

5.53

  

−306.42

614.83

617.48

1

.75

 

2

0.17

6.65

6.48

−150.89

311.77

325.00

5

 

F

1

0.58

  

−147.10

296.20

298.84

1

.90

 

2

0.00

2.20

2.20

−72.26

154.51

167.73

5

 

G

1

1.20

  

−311.46

624.91

627.55

1

.94

 

2

0.03

7.18

7.15

−51.94

113.89

127.11

5

 
  1. Note. Θ mean number of symptoms per mode, Θ2 Θ1 = distance between the modes, logl log likelihood, AIC Akaike’s Information Criterion, BIC Bayesian Information Criterion, nfree number of freely estimated parameters, BC Bimodality Coefficient