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Table 4 Results of the sequential process of assessing measurement invariance of the EPIC-26

From: Validation of the Italian version of the abbreviated expanded prostate Cancer index composite (EPIC-26) in men with prostate Cancer

Model

SB Χ2

df

p

RMSEA

CFI

TLI

SRMR

ΔCFI

Configural Invariance

1892.249

1105

.000

.044

.913

.904

.062

Metric Invariance

2003.830

1125

.000

.047

.903

.895

.068

- .010

Scalar Invariance

2279.990

1145

.000

.052

.875

.866

.071

- .028

Partial Scalar Invariance - Item 14

2225.603

1144

.000

.051

.881

.872

.071

- .022

Partial Scalar Invariance – Item 5

2196.445

1143

.000

.051

.884

.876

.070

- .019

Partial Scalar Invariance – Item 25

2155.922

1142

.000

.050

.888

.880

.070

- .015

Partial Scalar Invariance – Item 6

2126.187

1141

.000

.049

.891

.883

.069

- .012

Partial Scalar Invariance – Item 21

2101.490

1140

.000

.048

.894

.886

.069

- .009

Residual Variance Invariance

2232.515

1160

.000

.051

.882

.875

.078

- .012

Partial Residual Variance Invariance – Item 13

2219.857

1159

.000

.050

.883

.876

.075

- .011

Partial Residual Variance Invariance – Item 22

2167.399

1158

.000

.049

.889

.882

.072

- .005

Factor Variance Invariance

2191.584

1163

.000

.050

.887

.881

.077

- .002

Factor Covariance Invariance

2231.046

1173

.000

.050

.883

.878

.078

- .004

Factor Mean Invariance

2562.749

1178

.000

.057

.847

.841

.098

- .036

Partial Factor Mean Invariance – Urinary Incontinence

2383.217

1177

.000

.053

.867

.862

.081

- .016

Partial Factor Mean Invariance – Urinary Irritation

2291.617

1176

.000

.051

.877

.872

.078

- .006

  1. The best fitting model for each of the seven steps of measurement invariance assessment is indicated in bold
  2. Note: SB Satorra-Bentler Chi Square, df degree of freedom, RMSEA Root mean square error of approximation, CFI Comparative fit index, TLI Tucker-Lewis index (TLI), SRMR Standardized root mean square residual, ΔCFI Difference in CFI between models