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Table 3 Results of tests of invariance for the VETERAN (N = 314) and DOPPS (N = 3,300) samples

From: Measurement invariance of the kidney disease and quality of life instrument (KDQOL-SF) across Veterans and non-Veterans

   

Comparative Statistics

Model

χ 2

df

Contrast with Model #

Δ χ 2

Δ df

Unadj. p <

Bonf. Adj. p <

ΔCFI

w 2

1. Baseline model: Two factors (KDCS & SF-36) with no invariance constraints

2796.225

178

- -

- -

- -

- -

- -

- -

- -

2. KDCS factor loadings invariant

2819.092

184

1

22.867

6

.00085

.025

.0003

.08

3. SF-36 factor loadings invariant

2804.771

185

1

8.546

7

.29

ns

.0002

.05

4. KDCS Burden subscale loading invariant

2796.239

179

1

0.014

1

.91

ns

<.0001

<.01

5. KDCS Social Interaction subscale loading invariant

2799.730

179

1

3.505

1

.062

ns

.0004

.03

6. KDCS Cognitive subscale loading invariant

2796.928

179

1

0.703

1

.41

ns

<.0001

.01

7. KDCS Effects subscale loading invariant

2798.687

179

1

2.462

1

.12

ns

.0005

.03

8. KDCS Sleep subscale loading invariant

2811.091

179

1

14.866

1

.00012

.0036

.0003

.06

9. KDCS Social Support subscale loading invariant

2803.528

179

1

7.303

1

.0069

ns

.0001

.04

10. Partially metric invariant model (factor loadings for KDCS Sleep & Social Support subscales noninvariant)

2810.567

189

1

14.342

11

.22

ns

.0003

.06

11. Partially invariant model with 5 metric invariant KDCS subscale intercepts invariant

2894.471

194

10

83.904

5

.000001

.00005

.0019

.15

12. Partially invariant model with 8 metric invariant SF36 subscale intercepts invariant

2964.251

197

10

153.684

8

.000001

.00005

.0040

.21

13. Partially invariant model with intercept of KDCS Burden subscale invariant

2812.836

190

10

2.269

1

.14

ns

.0003

.03

14. Partially invariant model with intercept of KDCS Social Interaction subscale invariant

2838.461

190

10

27.894

1

.000001

.00005

.0008

.09

15. Partially invariant model with intercept of KDCS Cognitive subscale invariant

2835.202

190

10

24.635

1

.000001

.00005

.0007

.08

16. Partially invariant model with intercept of KDCS Symptoms subscale invariant

2877.711

190

10

67.144

1

.000001

.00005

.0015

.14

17. Partially invariant model with intercept of KDCS Effects subscale invariant

2839.951

190

10

29.384

1

.000001

.00005

.0008

.09

18. Partially invariant model with intercept of SF-36 PF subscale invariant

2815.734

190

10

5.167

1

.024

ns

.0004

.04

19. Partially invariant model with intercept of SF-36 RP subscale invariant

2846.345

190

10

35.778

1

.000001

.00005

.0001

.10

20. Partially invariant model with intercept of SF-36 BP subscale invariant

2819.639

190

10

9.072

1

.0026

ns

.0004

.05

21. Partially invariant model with intercept of SF-36 GH subscale invariant

2810.568

190

10

0.001

1

.98

ns

.0003

<.01

22. Partially invariant model with intercept of SF-36 MH subscale invariant

2837.769

190

10

27.202

1

.000001

.00005

.0008

.09

23. Partially invariant model with intercept of SF-36 RE subscale invariant

2900.352

190

10

89.785

1

.000001

.00005

.0018

.16

24. Partially invariant model with intercept of SF-36 SF subscale invariant

2831.587

190

10

21.020

1

.000005

.00016

.0007

.08

25. Partially invariant model with intercept of SF-36 VT subscale invariant

2810.914

190

10

0.347

1

.56

ns

.0003

<.01

26. Partially metric invariant model with two-factor variances & covariance invariant

2816.786

192

10

6.219

3

.11

ns

.0005

.04

27. Partially metric invariant model with factor variances-covariance & unique error variances for KDCS subscales invariant

2866.086

199

26

49.300

7

.000001

.00005

.0007

.12

28. Partially metric invariant model with factor variances-covariance & unique error variances for SF-36 subscales invariant

2840.570

200

26

23.784

8

.0025

ns

<.0001

.09

29. Partially metric invariant model with factor variances-covariance & unique error variance for KDCS Burden subscale invariant

2827.202

193

26

10.416

1

.0013

.036

.0003

.07

30. Partially metric invariant model with factor variances-covariance & unique error variance for KDCS Social Interaction subscale invariant

2816.909

193

26

0.123

1

.73

ns

.0006

.01

31. Partially metric invariant model with factor variances-covariance & unique error variance for KDCS Cognitive subscale invariant

2821.228

193

26

4.442

1

.036

ns

.0001

.04

32. Partially metric invariant model with factor variances-covariance & unique error variance for KDCS Symptoms subscale invariant

2825.083

193

26

8.297

1

.004

ns

.0001

.05

33. Partially metric invariant model with factor variances-covariance & unique error variance for KDCS Effects subscale invariant

2816.917

193

26

0.131

1

.72

ns

.0006

.01

34. Partially metric invariant model with factor variances-covariance & unique error variance for KDCS Sleep subscale invariant

2838.330

193

26

21.544

1

.000004

.00013

<.0001

.08

35. Partially metric invariant model with factor variances-covariance & unique error variance for KDCS Social Support subscale invariant

2821.074

193

26

4.288

1

.039

ns

.0009

.03

36. Partially metric invariant model with factor variances-covariance & unique error variance for SF-36 PF subscale invariant

2817.060

193

26

0.274

1

.61

ns

.0006

.01

37. Partially metric invariant model with factor variances-covariance & unique error variance for SF-36 RP subscale invariant

2818.194

193

26

1.408

1

.24

ns

.0004

.02

38. Partially metric invariant model with factor variances-covariance & unique error variance for SF-36 BP subscale invariant

2816.855

193

26

0.069

1

.80

ns

.0007

<.01

39. Partially metric invariant model with factor variances-covariance & unique error variance for SF-36 GH subscale invariant

2819.464

193

26

2.678

1

.11

ns

.0003

.03

40. Partially metric invariant model with factor variances-covariance & unique error variance for SF-36 MH subscale invariant

2817.791

193

26

1.005

1

.32

ns

.0009

.02

41. Partially metric invariant model with factor variances-covariance & unique error variance for SF-36 RE subscale invariant

2821.873

193

26

5.087

1

.025

ns

.0011

.09

42. Partially metric invariant model with factor variances-covariance & unique error variance for SF-36 SF subscale invariant

2821.253

193

26

4.467

 

.035

ns

.0002

.04

43. Partially metric invariant model with factor variances-covariance & unique error variance for SF-36 VT subscale invariant

2826.729

193

26

9.943

 

.0017

.045

.0002

.05

  1. Note: CFI = Comparative fit index. W2 = ratio of chi-square divided by N [68], which is analogous to R-squared (i.e., the proportion of explained variance) in multiple regression. Cohen [68] suggested that w2 ≤ 0.01 is small, w2 = 0.09 is medium, and w2 ≥ 0.25 is large.
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Health and Quality of Life Outcomes

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