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Table 3 Fit indices of 1-factor BSEM measurement invariance models for the Urbanicity Scale

From: Longitudinal measurement invariance in urbanization index of Chinese communities across 2000 and 2015: a Bayesian approximate measurement invariance approach

Model specification

Prior variance

pD

2.5%

PPL

97.5%

PPL

RMSEA

CFI

ΔRMSEA

ΔCFI

2000–2015 (N = 301):

 Configural

/

389

631.5

1101.6

0.000

1.000

/

/

 Metric

Exact

309

1123.6

1584.5

0.024

0.975

+ 0.024

−0.025

 Metric

V = 0.01

323

819.4

1276.3

0.012

0.994

+ 0.012

− 0.006

 Scalar

Exact

268

2505.7

3004.3

0.050

0.887

+ 0.038

− 0.107

 Scalar

V = 0.01

280

1791.9

2250.2

0.039

0.933

+ 0.027

−0.061

 Scalar

V = 0.04

302

1070.4

1518.8

0.022

0.978

+ 0.010

−0.016

 Scalar

V = 0.09

311

897.6

1350.6

0.016

0.989

+ 0.004

−0.005

2004–2011 (N = 295):

 Configural

/

214

264.0

564.1

0.012

0.996

/

/

 Metric

Exact

173

450.5

732.2

0.027

0.979

+ 0.015

−0.017

 Metric

V = 0.01

181

329.5

619.5

0.018

0.990

+ 0.006

−0.006

 Scalar

Exact

144

1062.4

1368.9

0.052

0.920

+ 0.034

−0.070

 Scalar

V = 0.01

160

580.9

869.3

0.034

0.966

+ 0.016

−0.024

 Scalar

V = 0.04

171

380.3

674.0

0.023

0.985

+ 0.005

−0.005

2006–2009 (N = 220):

 Configural

/

84

41.6

170.5

0.046

0.972

/

/

 Metric

Exact

72

66.9

192.1

0.050

0.965

+ 0.004

−0.007

 Scalar

Exact

61

220.9

339.1

0.071

0.928

+ 0.021

−0.037

 Scalar

V = 0.01

66

103.2

229.1

0.056

0.956

+ 0.006

−0.009

  1. PPL posterior predictive limit, pD Estimated number of parameters, RMSEA root mean square error of approximation, CFI comparative fit index; Δ = change in fit index over the previous nested (bolded) model