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Table 2 Principal component analysis on APPRSQ

From: Virtual classes during COVID-19 pandemic: focus on university students’ affection, perceptions, and problems in the light of resiliency and self-image

Component

Initial eigenvalues

Extraction sums of squared loadings

Rotation sums of squared loadingsa

Total

% of variance

Cumulative %

Total

% of variance

Cumulative %

Total

1

14.523

39.251

39.251

14.523

39.251

39.251

11.598

2

6.904

18.659

57.910

6.904

18.659

57.910

7.664

3

2.545

6.877

64.787

2.545

6.877

64.787

4.364

4

1.535

4.149

68.936

1.535

4.149

68.936

9.644

5

1.148

3.102

72.038

1.148

3.102

72.038

8.433

6

.846

2.285

74.323

    

7

.746

2.016

76.339

    

8

.717

1.937

78.277

    

9

.621

1.680

79.956

    

10

.601

1.624

81.580

    

11

.563

1.521

83.101

    

12

.525

1.418

84.519

    

13

.492

1.329

85.848

    

14

.459

1.242

87.090

    

15

.421

1.139

88.229

    

16

.356

.961

89.190

    

17

.344

.929

90.118

    

18

.331

.894

91.012

    

19

.303

.819

91.831

    

20

.293

.793

92.623

    

21

.281

.758

93.382

    

22

.273

.737

94.119

    

23

.265

.717

94.836

    

24

.227

.613

95.449

    

25

.209

.564

96.013

    

26

.200

.540

96.553

    

27

.184

.498

97.051

    

28

.168

.455

97.506

    

29

.148

.401

97.906

    

30

.135

.366

98.272

    

31

.124

.335

98.607

    

32

.121

.326

98.933

    

33

.105

.285

99.218

    

34

.095

.257

99.475

    

35

.079

.213

99.688

    

36

.072

.194

99.882

    

37

.044

.118

100.000

    
  1. Extraction method: principal component analysis
  2. aWhen components are correlated, sums of squared loadings cannot be added to obtain a total variance