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Table 3 Results of factor analysis

From: Japanese Orthopaedic Association Cervical Myelopathy Evaluation Questionnaire (JOACMEQ) in mainland China: an investigation of reliability, validity, and responsiveness

Factor

Initial eigenvalues

Rotation sums of squared loadings

Eigenvalue

Contribution rate (%)

Cumulative contribution rate (%)

Eigenvalue

Contribution rate (%)

Cumulative contribution rate (%)

1

7.671

31.963

31.963

4.653

19.387

19.387

2

2.422

10.091

42.055

4.522

18.841

38.228

3

1.923

8.014

50.069

2.277

9.487

47.715

4

1.720

7.168

57.236

1.953

8.136

55.851

5

1.249

5.205

62.441

1.582

6.590

62.441

6

1.080

4.501

66.942

   

7

0.947

3.944

70.886

   

8

0.876

3.650

74.536

   

9

0.763

3.179

77.715

   

10

0.694

2.892

80.607

   

11

0.654

2.727

83.334

   

12

0.594

2.475

85.809

   

13

0.506

2.108

87.917

   

14

0.410

1.707

89.624

   

15

0.364

1.515

91.139

   

16

0.346

1.444

92.582

   

17

0.317

1.320

93.902

   

18

0.298

1.241

95.143

   

19

0.270

1.124

96.267

   

20

0.254

1.059

97.326

   

21

0.204

0.848

98.174

   

22

0.187

0.778

98.952

   

23

0.134

0.558

99.509

   

24

0.118

0.491

100.000

   
  1. Eigenvalues are shown in italics, which represent the total amount of variance that can be explained by a given principal component. In factor analysis, only factors with eigenvalues of 1.00 or higher are traditionally considered worth analyzing, because eigenvalue above 1 means this factor can explain more than 1 variance
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