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Table 4 Akaike information criterion output – to appear between lines 194 and 195

From: Population-level predictors of sexually transmitted infection rate changes in Missouri: an ecological study

 

Model

AIC

ΔAIC

Wia

R2

Chlamydia

Population growth + unemployment + income

− 135

0

0.2893

0.41

Unemployment + income

− 134.92

0.0887

0.2767

0.40

Population change + unemployment + income

−133.912

0.0887

0.2768

0.41

Population growth + population size + unemployment + income

− 133.10

1.9016

0.1118

0.42

Income

− 131.962

3.0279

  

Population growth + income

−131.096

3.9044

  

Population size + income

− 130.773

4.2276

  

Population growth + population size + income

− 129.617

5.3828

  

Population size

− 105.627

29.3727

  

Population growth + population size

− 104.388

30.6119

  

Population growth + population size + unemployment

− 102.558

32.4423

  

Population growth

−78.0372

56.9630

  

Population growth + unemployment

−76.0378

58.9624

  

Intercept of values

−75.4091

59.5911

  

unemployment

−73.5686

61.4316

  

Gonorrhea

Population size + unemployment + income

− 324.99

0

0.43552

0.41

Unemployment + incomes

−324.096

0.8944

0.27848

0.38

Population growth + population size + unemployment + income

− 323.004

1.9863

0.16132

0.41

Population growth + unemployment + income

− 322.153

2.8378

  

Population size + income

−317.481

7.5093

  

Population growth + population size + income

− 315.911

9.0795

  

Income

−315.172

9.8185

  

Population growth + income

−313.239

11.7515

  

Population size

−303.001

21.9892

  

Population growth population size

− 301.317

23.6733

  

Population growth + population size + unemployment

−301.243

23.7476

  

Intercept of values

− 266.903

58.0875

  

Population growth

−266.008

58.9828

  

Unemployment

− 265.217

59.7735

  

Population growth + unemployment

− 264.630

60.3605

  

Syphilis

Unemployment + income

− 879.245

0

0.465195

0.43

Population size + unemployment + income

− 877.925

1.3198

0.240561

0.44

Population growth + unemployment + income

−877.397

1.8481

0.18464

0.42

Population growth + population size + unemployment + income

−875.976

3.2695

  

Income

− 871.049

8.1963

  

Population size + income

− 870.563

8.6818

  

Population growth + income

− 869.059

10.1865

  

Population growth + population size + income

− 868.672

10.5733

  

Population size

−846.402

32.8431

  

Population growth + population size

− 844.457

34.7877

  

Population growth + population size + unemployment

−843.496

35.7494

  

Intercept of values

− 812.970

66.2754

  

Population growth

−812.585

66.6605

  

Unemployment

− 811.029

68.2165

  

Population growth + unemployment

− 810.843

68.4023

  

HIV

Unemployment + income

− 250.519

0

0.52521

0.37

Population size + unemployment + income

− 248.600

1.9192

0.20118

0.37

Population growth + unemployment + income

−248.535

1.984

0.19477

0.37

Population growth + population size + unemployment + income

−246.604

3.9144

  

Income

−239.578

10.9404

  

Population size + income

− 238.168

12.3504

  

Population growth + income

−237.742

12.7764

  

Population growth + population size + income

− 236.476

14.0424

  

Population size

− 220.601

29.9180

  

Population growth + population size + unemployment

−219.483

31.0360

  

Population growth + population size

− 218.810

31.7084

  

Intercept of values

−197.583

52.9358

  

Unemployment

−196.471

54.0479

  

Population growth

−196.324

54.1943

  

Population growth + unemployment

−195.626

54.8925

  
  1. Where AIC is Akaike Information Criterion value, ΔAIC is the change in Akaike Information Criterion value, Wi is the Akaike weights value, and R2 is the correlational coefficient
  2. Presents a test of model fitness for all county variables and their ability to predict STI rate changes. This table also presents the best fit models, where the selected variables do the best job at predicting the STI rate change, as indicated in bold print
  3. awi and R2 were calculated for only those models considered to be of best fit