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C1
REX B KLINE CONCORDIA
C. MEASUREMENT INVARIANCE
SEM ADVANCED
C2
C3
1 model
≥ 2 data sets
simultaneous
mu
ltip
le
C4
≥ 2 populations
≥ 2 occasions
≥ 2 methods
mu
ltip
le
C5
unstandardized
constrain to equal
fit to data
mu
ltip
le
C6
fit, yes
conclude, equal
no? release
mu
ltip
le
C7
2
Dχ
n
n
mu
ltip
le
C8
Levels
Dimensional
Configural
Weak (Metric)
Strong (Scalar)
Strict (Error)
C9
Dimensional
1
A
1
X1
E1
1
X2
E2
1
X3
E3
1
B
1
X4
E4
1
X5
E5
1
X6
E6
1
1
X1
E1
1
X2
E2
1
X3
E3
A´
1
1
X4
E4
1
X5
E5
1
X6
E6
B´
C10
Configural
Same no. factors, match
No other constraints
Different scoring systems
C11
Weak
Assumes configural
Equal pattern coefficients
Same scoring system
C12
Strong
Assumes weak
Equal intercepts, thresholds
Same response level
C13
Strict
Assumes strong
Same error variance
Identical measurement
C14
DeShon, R. P. (2004). Measures are not invariant across
groups without error variance homogeneity.
Psychology Science, 46, 137–149.
Wu, A. D., Li, Z., & Zumbo, B. D. (2007). Decoding the
meaning of factorial Invariance and updating the
practice of multi-group confirmatory factor analysis: A
demonstration with TIMSS data. Practical Assessment
Research & Evaluation, 12(3). Retrieved from
http://pareonline.net/pdf/v12n3.pdf
C15
Partial invariance (1)
Configural retained
Weak: Some, not all
DIF (1)
C16
1
X
DX 1
A
C17
Partial invariance (1)
Different relative meaning
Extreme response sets
C18
Ryder, A. G., Yang J., Zhu, X., Yao, S., Yi, J.,
Heine, S. J., & Bagby, R. M. (2009). The
cultural shaping of depression: Somatic
symptoms in China, psychological
symptoms in North America? Journal of
Abnormal Psychology, 117, 300–313.
C19
Cheung, G. W., & Rensvold, R. B. (2000).
Assessing extreme and acquiescence
response sets in cross-cultural research
using structural equations modeling.
Journal of Cross-Cultural Psychology, 31,
187–212.
C20
Partial invariance (2)
Configural retained
Strong: Some, not all
DIF (2)
C21
1
X
DX 1
A
C22
Partial invariance (2)
Differential additive response
Cultural, gender, procedural
C23
Gregorich, S. E. (2006). Do self-report
instruments allow meaningful
comparisons across diverse population
groups? Testing measurement invariance
using the confirmatory factor analysis
framework. Medical Care, 44 (Suppl. 3),
S78–S94.
C24
2
Dχ
Low power, n < 400
Very large n . . .
CFI, Δ ≤ .01 rule
C25
Chen, F. F. (2007). Sensitivity of goodness of
fit indexes to lack of measurement
invariance. Structural Equation Modeling,
14, 464–504.
C26
Sequence (1)
Configural → Weak → Strong → Strict
Free baseline approach
Model trimming
C27
Sequence (2)
Strict → . . . ?
Constrained baseline approach
Model building
C28
Millsap, R. E., & Olivera-Aguilar, M. (2012).
Investigating measurement invariance
using confirmatory factor analysis. In R. H.
Hoyle (Ed.), Handbook of structural
equation modeling (pp. 380–392). New
York: Guilford.
C29
Example
Hispanic with teenagers
English, n1 = 193
Spanish, n2 = 257
C30
English
Item fc1 fc4 fc5 fc6 fc9 M SD
fc1 — .381 .599 .416 .601 2.280 .887
fc4 .227 — .393 .445 .404 1.518 .925
fc5 .400 .322 — .476 .661 2.052 .972
fc6 .324 .330 .354 — .519 1.689 1.014
fc9 .473 .370 .486 .540 — 1.684 .901
Spanish M 2.113 1.175 1.708 1.366 1.319
SD 1.034 .597 .836 .785 .701
Note. English-speaking (above diagonal; n1 = 193), Spanish-speaking
(below diagonal; n2 = 257).
C31
fc9
1 E9
fc6
1 E6
fc5
1 E5
fc4
1 E4
fc1
1 E1
Conflict 1
C32
Little, T. D., Slegers, D. W., & Card, N. A.
(2006). A non-arbitrary method of
identifying and scaling latent variables in
SEM and MACS models. Structural
Equation Modeling, 13, 59–72.
C33
Reference group
0 1
fc9
1 E9
fc6
1 E6
fc5
1 E5
fc4
1 E4
fc1
1 E1
Conflict 1
C34
Marker variable
1
fc9
1 E9
fc6
1 E6
fc5
1 E5
fc4
1 E4
fc1
1 E1
Conflict 1
0
C35
Effects coding (1)
λ1
fc9
1 E9
fc6
1 E6
fc5
1 E5
fc4
1 E4
fc1
1 E1
Conflict
λ2 λ3 λ4 λ5
1
C36
1 2 3 4 5 1
5
1 2 3 4 55
2 1 3 4 55
3 1 2 4 55
4 1 2 3 55
5 1 2 3 45
C37
Effects coding (2)
Conflict
fc9
1 E9
fc6
1 E6
fc5
1 E5
fc4
1 E4
fc1
1 E1
1
τ1 τ2 τ3 τ4 τ5
C38
1 2 3 4 5 0
5
1 2 3 4 50
2 1 3 4 50
3 1 2 4 50
4 1 2 3 50
5 1 2 3 40
C39
Models
1. Configural (M1)
2. M1 with error correlation (M2)
3. M2 with full metric (M3)
4. M3 with full error (M4)
5. M3 with full scalar (M5)
6. M3 with partial scalar (M6)
C40
Model 1 (No)
× 2
C41
Model 2 (Yes)
C42
Model 3 (Yes)
C43
Model 4 (No)
C44
Model 5 (No)
C45
Model 6 (Yes)
C46
Model
2Mχ dfM
2Dχ dfD Comparison RMSEA 90% CI
1 (N) 15.36 10 — — .049 0 – .095
2 (Y) 7.85 9 7.51** 1 2 vs. 1 0 0 – .068
3 (Y) 13.36 13 5.51* 4 3 vs. 2 .011 0 – .068
4 (N) 87.57** 18 74.21** 5 4 vs. 3 .131 .104 – .159
5 (N) 22.72 17 9.36 4 5 vs. 3 .039 0 – .076
6 (Y) 13.46 15 .10 2 6 vs. 3 0 0 – .057
C47
Model 1
Observations
v (v + 3)/2 × no. groups
5(8)/2 × 2 = 40
fc9
1 E9
fc6
1 E6
fc5
1 E5
fc4
1 E4
fc1
1 E1
Conflict 1
C48
Parameters
Variances: (5 + 1) × 2 = 12
Loadings: (4) × 2 = 8
Intercepts = (4) × 2 = 8
Means = 2
dfM = 40 − 30 = 10
fc9
1 E9
fc6
1 E6
fc5
1 E5
fc4
1 E4
fc1
1 E1
Conflict 1
C49
C50
LISREL “classic”
Sorry, SIMPLIS
Mplus
C51
C52
Mplus defaults
1st indicator, loading = 1
Other loadings free but equal
Intercepts free but equal
C53
Mplus defaults
Factor, error vars. & covs. free
1st group, factor mean = 0
Otherwise free and unequal
C54
title:
dillman data
model 1
configural invariance
data:
file is dillman.dat;
type is means std corr;
nobservations = 193 257;
ngroups = 2;
! group 1 is english, group 2 is spanish
variable:
names = fc1 fc4 fc5 fc6 fc9;
analysis:
type = general; estimator = ml;
C55
model:
! names group 1 factor loadings:
Conflict by fc1* (g1_load1)
fc4 (g1_load2)
fc5 (g1_load3)
fc6 (g1_load4)
fc9 (g1_load5);
! names group 1 intercepts:
[fc1] (g1_int1);
[fc4] (g1_int2);
[fc5] (g1_int3);
[fc6] (g1_int4);
[fc9] (g1_int5);
model g1:
! group 1 factor mean is free parameter:
[Conflict];
C56
model g2:
! names group 2 factor loadings
! separate loadings estimated in group 2:
Conflict by fc1* (g2_load1)
fc4 (g2_load2)
fc5 (g2_load3)
fc6 (g2_load4)
fc9 (g2_load5);
! names group 2 factor loadings
! separate intercepts estimated in group 2:
[fc1] (g2_int1);
[fc4] (g2_int2);
[fc5] (g2_int3);
[fc6] (g2_int4);
[fc9] (g2_int5);
C57
! separate factor mean, variance in group 2:
Conflict;
[Conflict];
! by default, measurement errors are freely
! estimated in each group
model constraint:
! effects-coding method for scaling
! and identifying factor
! average loading constrained to 1.0 and
! average intercept constrained to 0
C58
! group 1:
g1_load1 = 5 - g1_load2 - g1_load3 - g1_load4 - g1_load5;
g1_int1 = -g1_int2 - g1_int3 - g1_int4 - g1_int5;
! group 2:
g2_load1 = 5 - g2_load2 - g2_load3 - g2_load4 - g2_load5;
g2_int1 = -g2_int2 - g2_int3 - g2_int4 - g2_int5;
output: samp stdyx res;
C59
THE MODEL ESTIMATION TERMINATED NORMALLY
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 15.363
Degrees of Freedom 10
P-Value 0.1194
Chi-Square Contributions From Each Group
G1 8.991
G2 6.372
C60
CFI/TLI
CFI 0.991
TLI 0.983
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.049
90 Percent C.I. 0.000 0.095
SRMR (Standardized Root Mean Square Residual)
Value 0.026
C61
RESIDUAL OUTPUT
ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR G1
Model Estimated Covariances/Correlations/Residual Correlations
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
FC1 0.783
FC4 0.312 0.851
FC5 0.499 0.373 0.940
FC6 0.406 0.304 0.487 1.023
FC9 0.477 0.357 0.572 0.465 0.808
Residuals for Covariances/Correlations/Residual Correlations
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
FC1 0.000
FC4 -0.001 0.000
FC5 0.014 -0.022 0.000
FC6 -0.034 0.112 -0.020 0.000
FC9 0.001 -0.022 0.004 0.007 0.000
C62
ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR G1
Standardized Residuals (z-scores) for Covariances/Correlations/Residual Corr
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
FC1 0.014
FC4 -0.019 0.000
FC5 0.843 -0.924 0.000
FC6 -1.365 2.466 -0.941 0.000
FC9 0.055 -1.151 0.396 0.324 999.000
C63
ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR G2
Model Estimated Covariances/Correlations/Residual Correlations
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
FC1 1.065
FC4 0.164 0.355
FC5 0.298 0.141 0.696
FC6 0.293 0.139 0.252 0.614
FC9 0.338 0.160 0.292 0.287 0.489
Residuals for Covariances/Correlations/Residual Correlations
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
FC1 0.000
FC4 -0.024 0.000
FC5 0.047 0.019 0.000
FC6 -0.031 0.015 -0.021 0.000
FC9 0.003 -0.006 -0.008 0.009 0.000
C64
ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR G2
Standardized Residuals (z-scores) for Covariances/Correlations/Residual Corr
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
FC1 999.000
FC4 -1.011 0.000
FC5 1.548 0.978 0.000
FC6 -1.301 0.884 -1.195 0.000
FC9 0.305 -0.880 -1.265 1.183 0.000
C65
PAGE : 6 EQS
TITLE: Group 1: English
MULTIPLE POPULATION ANALYSIS, INFORMATION IN GROUP 1
MAXIMUM LIKELIHOOD SOLUTION (NORMAL DISTRIBUTION THEORY)
LARGEST STANDARDIZED RESIDUALS:
NO. PARAMETER ESTIMATE NO. PARAMETER ESTIMATE
--- --------- -------- --- --------- --------
1 V4, V2 .119 11 V4, V4 .000
2 V4, V1 -.038 12 V2, V2 .000
3 V5, V2 -.026 13 V3, V3 .000
4 V3, V2 -.024 14 V5, V5 .000
5 V4, V3 -.020 15 V999,V4 .000
6 V3, V1 .017 16 V999,V5 .000
7 V5, V4 .007 17 V999,V2 .000
8 V5, V3 .005 18 V999,V3 .000
9 V5, V1 .001 19 V999,V1 .000
10 V2, V1 -.001 20 V1, V1 .000
C66
PAGE : 12 EQS
TITLE: Group 2: Spanish
MULTIPLE POPULATION ANALYSIS, INFORMATION IN GROUP 2
MAXIMUM LIKELIHOOD SOLUTION (NORMAL DISTRIBUTION THEORY)
LARGEST STANDARDIZED RESIDUALS:
NO. PARAMETER ESTIMATE NO. PARAMETER ESTIMATE
--- --------- -------- --- --------- --------
1 V3, V1 .054 11 V5, V5 .000
2 V2, V1 -.039 12 V4, V4 .000
3 V3, V2 .038 13 V3, V3 .000
4 V4, V1 -.038 14 V2, V2 .000
5 V4, V2 .033 15 V999,V5 .000
6 V4, V3 -.032 16 V999,V4 .000
7 V5, V4 .017 17 V999,V3 .000
8 V5, V2 -.015 18 V999,V2 .000
9 V5, V3 -.014 19 V999,V1 .000
10 V5, V1 .005 20 V1, V1 .000
C67
Model 2 (Yes)
C68
title:
dillman-carpentier
model 2
configural invariance with error correlation
group 1, fc4 and fc6
...
model g1:
! group 1 factor mean is free parameter:
[Conflict];
! ** new to model 2 **
! error covariance group 1 only:
fc4 with fc6;
C69
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 7.850
Degrees of Freedom 9
P-Value 0.5493
Chi-Square Contributions From Each Group
G1 1.478
G2 6.372
C70
CFI/TLI
CFI 1.000
TLI 1.004
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000
90 Percent C.I. 0.000 0.068
SRMR (Standardized Root Mean Square Residual)
Value 0.018
C71
RESIDUAL OUTPUT
ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR G1
Standardized Residuals (z-scores) for Covariances/Correlations/Residual Corr
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
FC1 999.000
FC4 0.487 0.032
FC5 0.617 -0.195 999.000
FC6 -0.847 0.020 -0.321 0.010
FC9 -0.401 -0.257 -0.437 0.916 999.000
C72
ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR G2
Standardized Residuals (z-scores) for Covariances/Correlations/Residual Corr
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
FC1 999.000
FC4 -1.011 0.000
FC5 1.547 0.977 0.000
FC6 -1.302 0.884 -1.195 999.000
FC9 0.305 -0.880 -1.265 1.184 999.000
C73
PAGE : 6 EQS
TITLE: Group 1: English
MULTIPLE POPULATION ANALYSIS, INFORMATION IN GROUP 1
MAXIMUM LIKELIHOOD SOLUTION (NORMAL DISTRIBUTION THEORY)
LARGEST STANDARDIZED RESIDUALS:
NO. PARAMETER ESTIMATE NO. PARAMETER ESTIMATE
--- --------- -------- --- --------- --------
1 V4, V1 -.025 11 V4, V2 .000
2 V5, V4 .021 12 V4, V4 .000
3 V2, V1 .018 13 V3, V3 .000
4 V3, V1 .011 14 V2, V2 .000
5 V4, V3 -.007 15 V1, V1 .000
6 V5, V2 -.006 16 V999,V5 .000
7 V3, V2 -.005 17 V999,V2 .000
8 V5, V1 -.005 18 V999,V4 .000
9 V5, V3 -.003 19 V999,V1 .000
10 V5, V5 .000 20 V999,V3 .000
C74
PAGE : 14 EQS
TITLE: Group 2: Spanish
MULTIPLE POPULATION ANALYSIS, INFORMATION IN GROUP 2
MAXIMUM LIKELIHOOD SOLUTION (NORMAL DISTRIBUTION THEORY)
LARGEST STANDARDIZED RESIDUALS:
NO. PARAMETER ESTIMATE NO. PARAMETER ESTIMATE
--- --------- -------- --- --------- --------
1 V3, V1 .054 11 V5, V5 .000
2 V2, V1 -.039 12 V4, V4 .000
3 V3, V2 .038 13 V3, V3 .000
4 V4, V1 -.038 14 V2, V2 .000
5 V4, V2 .033 15 V999,V5 .000
6 V4, V3 -.032 16 V999,V4 .000
7 V5, V4 .017 17 V999,V3 .000
8 V5, V2 -.015 18 V999,V2 .000
9 V5, V3 -.014 19 V999,V1 .000
10 V5, V1 .005 20 V1, V1 .000
C75
Model 3 (Yes)
C76
title:
dillman-carpentier
model 3
metric invariance with error correlation
group 1, fc4 and fc6
...
C77
model g2:
! names group 2 factor loadings
! ** new to model 3 **
! pairwise equality constraints imposed on loadings
! by commenting out the following group 2 syntax:
! Conflict by fc1* (g2_load1)
! fc4 (g2_load2)
! fc5 (g2_load3)
! fc6 (g2_load4)
! fc9 (g2_load5);
...
C78
model constraint:
! effects-coding method for scaling
! and identifying factor
! average loading constrained to 1.0 and
! average intercept constrained to 0
! group 1:
g1_load1 = 5 - g1_load2 - g1_load3 - g1_load4 - g1_load5;
g1_int1 = -g1_int2 - g1_int3 - g1_int4 - g1_int5;
! group 2:
! ** new to model 3 **
! original group 2 constraint on loadings not needed
! and is commented out:
! g2_load1 = 5 - g2_load2 - g2_load3 - g2_load4 - g2_load5;
C79
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 13.361
Degrees of Freedom 13
P-Value 0.4203
Chi-Square Contributions From Each Group
G1 3.617
G2 9.744
C80
CFI/TLI
CFI 0.999
TLI 0.999
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.011
90 Percent C.I. 0.000 0.068
SRMR (Standardized Root Mean Square Residual)
Value 0.036
C81
RESIDUAL OUTPUT
ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR G1
Standardized Residuals (z-scores) for Covariances/Correlations/Residual Corr
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
FC1 999.000
FC4 0.744 0.850
FC5 0.404 1.019 1.079
FC6 -1.764 0.565 0.028 -0.626
FC9 -3.828 0.675 0.839 -0.074 -0.274
C82
ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR G2
Standardized Residuals (z-scores) for Covariances/Correlations/Residual Corr
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
FC1 1.205
FC4 -0.604 -1.958
FC5 1.356 -0.535 -2.635
FC6 0.402 0.354 -1.347 0.688
FC9 1.511 -1.508 -2.435 1.302 0.228
C83
PAGE : 6 EQS
TITLE: Group 1: English
MULTIPLE POPULATION ANALYSIS, INFORMATION IN GROUP 1
MAXIMUM LIKELIHOOD SOLUTION (NORMAL DISTRIBUTION THEORY)
LARGEST STANDARDIZED RESIDUALS:
NO. PARAMETER ESTIMATE NO. PARAMETER ESTIMATE
--- --------- -------- --- --------- --------
1 V4, V1 -.065 11 V4, V2 .021
2 V3, V2 .057 12 V3, V1 .013
3 V1, V1 -.048 13 V5, V5 -.007
4 V3, V3 .047 14 V5, V4 -.003
5 V5, V1 -.043 15 V4, V3 .001
6 V2, V1 .041 16 V999,V5 .000
7 V2, V2 .041 17 V999,V4 .000
8 V5, V2 .035 18 V999,V1 .000
9 V5, V3 .026 19 V999,V2 .000
10 V4, V4 -.023 20 V999,V3 .000
C84
PAGE : 14 EQS
TITLE: Group 2: Spanish
MULTIPLE POPULATION ANALYSIS, INFORMATION IN GROUP 2
MAXIMUM LIKELIHOOD SOLUTION (NORMAL DISTRIBUTION THEORY)
LARGEST STANDARDIZED RESIDUALS:
NO. PARAMETER ESTIMATE NO. PARAMETER ESTIMATE
--- --------- -------- --- --------- --------
1 V5, V1 .068 11 V4, V4 .026
2 V3, V1 .067 12 V3, V2 -.022
3 V3, V3 -.057 13 V4, V1 .020
4 V1, V1 .055 14 V4, V2 .016
5 V5, V3 -.055 15 V5, V5 .006
6 V4, V3 -.052 16 V999,V3 .000
7 V5, V2 -.048 17 V999,V2 .000
8 V5, V4 .047 18 V999,V1 .000
9 V2, V2 -.035 19 V999,V4 .000
10 V2, V1 -.031 20 V999,V5 .000
C85
Model 4 (No)
C86
title:
dillman-carpentier
model 4
metric invariance with error correlation
group 1, fc4 and fc6
equality of error variances
...
C87
model:
! names group 1 factor loadings:
Conflict by fc1* (g1_load1)
fc4 (g1_load2)
fc5 (g1_load3)
fc6 (g1_load4)
fc9 (g1_load5);
! names group 1 intercepts:
[fc1] (g1_int1);
[fc4] (g1_int2);
[fc5] (g1_int3);
[fc6] (g1_int4);
[fc9] (g1_int5);
! ** new to model 4 **
! names group 1 error variances:
fc1 (g1_err1);
fc4 (g1_err2);
fc5 (g1_err3);
fc6 (g1_err4);
fc9 (g1_err5);
C88
model g2:
! names group 2 factor loadings
! pairwise equality constraints imposed on loadings
! by commenting out the following group 2 syntax:
! Conflict by fc1* (g2_load1)
! fc4 (g2_load2)
! fc5 (g2_load3)
! fc6 (g2_load4)
! fc9 (g2_load5);
! names group 2 factor loadings
! separate intercepts estimated in group 2:
[fc1] (g2_int1);
[fc4] (g2_int2);
[fc5] (g2_int3);
[fc6] (g2_int4);
[fc9] (g2_int5);
! ** new to model 4 **
! names group 2 error variances:
fc1 (g2_err1);
fc4 (g2_err2);
fc5 (g2_err3);
fc6 (g2_err4);
fc9 (g2_err5);
C89
model constraint:
! effects-coding method for scaling
! and identifying factor
! average loading constrained to 1.0 and
! average intercept constrained to 0
! group 1:
g1_load1 = 5 - g1_load2 - g1_load3 - g1_load4 - g1_load5;
g1_int1 = -g1_int2 - g1_int3 - g1_int4 - g1_int5;
! group 2:
! original group 2 constraint on loadings not needed
! and is commented out:
! g2_load1 = 5 - g2_load2 - g2_load3 - g2_load4 - g2_load5;
g2_int1 = -g2_int2 - g2_int3 - g2_int4 - g2_int5;
! ** new to model 4 **
! constrain error variances:
g1_err1 = g2_err1;
g1_err2 = g2_err2;
g1_err3 = g2_err3;
g1_err4 = g2_err4;
g1_err5 = g2_err5;
C90
Chi-Square Test of Model Fit
Value 87.571
Degrees of Freedom 18
P-Value 0.0000
Chi-Square Contributions From Each Group
G1 42.617
G2 44.954
C91
CFI/TLI
CFI 0.888
TLI 0.876
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.131
90 Percent C.I. 0.104 0.159
SRMR (Standardized Root Mean Square Residual)
Value 0.122
C92
C93
Model 3 (Yes)
C94
Model 3 MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
Group G1
Residual Variances
FC1 0.355 0.047 7.592 0.000
FC4 0.651 0.069 9.397 0.000
FC5 0.353 0.049 7.207 0.000
FC6 0.648 0.073 8.825 0.000
FC9 0.249 0.041 6.021 0.000
Group G2
Residual Variances
FC1 0.682 0.043 15.807 0.000
FC4 0.808 0.036 22.353 0.000
FC5 0.572 0.047 12.283 0.000
FC6 0.685 0.043 15.951 0.000
FC9 0.384 0.051 7.570 0.000
C95
Model 5 (metric + scalar invariance)
C96
title:
dillman-carpentier
model 5
metric invariance with error correlation
group 1, fc4 and fc6
scalar invariance
...
C97
model g2:
! names group 2 factor loadings
! pairwise equality constraints imposed on loadings
! by commenting out the following group 2 syntax:
! Conflict by fc1* (g2_load1)
! fc4 (g2_load2)
! fc5 (g2_load3)
! fc6 (g2_load4)
! fc9 (g2_load5);
! names group 2 factor loadings
! separate intercepts estimated in group 2:
! ** new to model 5 **
! comment out naming of constraints in group 2
! now pairwise constrained to equal group 1 values:
![fc1] (g2_int1);
![fc4] (g2_int2);
![fc5] (g2_int3);
![fc6] (g2_int4);
![fc9] (g2_int5);
C98
model constraint:
! effects-coding method for scaling
! and identifying factor
! average loading constrained to 1.0 and
! average intercept constrained to 0
! group 1:
g1_load1 = 5 - g1_load2 - g1_load3 - g1_load4 - g1_load5;
g1_int1 = -g1_int2 - g1_int3 - g1_int4 - g1_int5;
! group 2:
! original group 2 constraint on loadings not needed
! and is commented out:
! g2_load1 = 5 - g2_load2 - g2_load3 - g2_load4 - g2_load5;
! ** new to model 5 **
! original group 2 constraint on loadings not needed
! g2_int1 = -g2_int2 - g2_int3 - g2_int4 - g2_int5;
C99
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 22.717
Degrees of Freedom 17
P-Value 0.1587
Chi-Square Contributions From Each Group
G1 7.779
G2 14.938
C100
CFI/TLI
CFI 0.991
TLI 0.989
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.039
90 Percent C.I. 0.000 0.076
SRMR (Standardized Root Mean Square Residual)
Value 0.046
C101
RESIDUAL OUTPUT
ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR G1
Model Estimated Means/Intercepts/Thresholds
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
2.334 1.410 2.052 1.664 1.676
Residuals for Means/Intercepts/Thresholds
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
-0.054 0.108 0.000 0.025 0.008
Standardized Residuals (z-scores) for Means/Intercepts/Thresholds
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
-2.418 2.272 -0.005 0.603 0.437
C102
ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED) FOR G2
Model Estimated Means/Intercepts/Thresholds
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
2.028 1.209 1.708 1.367 1.323
Residuals for Means/Intercepts/Thresholds
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
0.085 -0.034 0.000 -0.001 -0.004
Standardized Residuals (z-scores) for Means/Intercepts/Thresholds
FC1 FC4 FC5 FC6 FC9
________ ________ ________ ________ ________
2.060 -2.788 0.007 -0.040 -0.380
C103
PAGE : 6 EQS
TITLE: Group 1: English
MULTIPLE POPULATION ANALYSIS, INFORMATION IN GROUP 1
MAXIMUM LIKELIHOOD SOLUTION (NORMAL DISTRIBUTION THEORY)
LARGEST STANDARDIZED RESIDUALS:
NO. PARAMETER ESTIMATE NO. PARAMETER ESTIMATE
--- --------- -------- --- --------- --------
1 V999,V2 .117 11 V1, V1 -.021
2 V999,V1 -.061 12 V5, V3 .016
3 V4, V1 -.054 13 V5, V5 -.015
4 V3, V3 .042 14 V5, V4 -.015
5 V3, V2 .035 15 V999,V5 .009
6 V2, V1 .032 16 V5, V2 .008
7 V4, V4 -.032 17 V4, V3 -.007
8 V3, V1 .031 18 V2, V2 .006
9 V5, V1 -.027 19 V4, V2 -.001
10 V999,V4 .024 20 V999,V3 .000
C104
PAGE : 14 EQS
TITLE: Group 2: Spanish
MULTIPLE POPULATION ANALYSIS, INFORMATION IN GROUP 2
MAXIMUM LIKELIHOOD SOLUTION (NORMAL DISTRIBUTION THEORY)
LARGEST STANDARDIZED RESIDUALS:
NO. PARAMETER ESTIMATE NO. PARAMETER ESTIMATE
--- --------- -------- --- --------- --------
1 V5, V1 .088 11 V5, V4 .047
2 V3, V1 .085 12 V3, V2 -.037
3 V999,V1 .082 13 V4, V1 .034
4 V5, V2 -.068 14 V2, V1 -.031
5 V1, V1 .062 15 V4, V4 .027
6 V2, V2 -.061 16 V5, V5 .007
7 V999,V2 -.056 17 V999,V5 -.006
8 V3, V3 -.052 18 V999,V4 -.001
9 V5, V3 -.050 19 V999,V3 .000
10 V4, V3 -.049 20 V4, V2 .000
C105
Model 6 (metric + partial scalar)
C106
title:
dillman-carpentier
model 6
metric invariance with error correlation
group 1, fc4 and fc6
partial scalar invariance
...
C107
model g2:
! names group 2 factor loadings
! pairwise equality constraints imposed on loadings
! by commenting out the following group 2 syntax:
! Conflict by fc1* (g2_load1)
! fc4 (g2_load2)
! fc5 (g2_load3)
! fc6 (g2_load4)
! fc9 (g2_load5);
! names group 2 factor loadings
! separate intercepts estimated in group 2:
! ** new to model 6 **
! comment out naming of constraints in group 2
! for only 3 indicators:
[fc1] (g2_int1);
[fc4] (g2_int2);
![fc5] (g2_int3);
![fc6] (g2_int4);
![fc9] (g2_int5);
C108
TESTS OF MODEL FIT
Chi-Square Test of Model Fit
Value 13.462
Degrees of Freedom 15
P-Value 0.5667
Chi-Square Contributions From Each Group
G1 3.808
G2 9.654
C109
CFI/TLI
CFI 1.000
TLI 1.003
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000
90 Percent C.I. 0.000 0.057
SRMR (Standardized Root Mean Square Residual)
Value 0.036
C110
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
Group G1
CONFLICT BY
FC1 1.062 0.059 18.033 0.000
FC4 0.635 0.055 11.570 0.000
FC5 1.144 0.053 21.441 0.000
FC6 0.988 0.056 17.706 0.000
FC9 1.171 0.049 23.847 0.000
FC4 WITH
FC6 0.139 0.052 2.657 0.008
Group G2
CONFLICT BY
FC1 1.062 0.059 18.033 0.000
FC4 0.635 0.055 11.570 0.000
FC5 1.144 0.053 21.441 0.000
FC6 0.988 0.056 17.706 0.000
FC9 1.171 0.049 23.847 0.000
C111
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
Group G1
Residual Variances
FC1 0.355 0.047 7.592 0.000
FC4 0.651 0.069 9.395 0.000
FC5 0.354 0.049 7.262 0.000
FC6 0.648 0.073 8.821 0.000
FC9 0.249 0.041 6.040 0.000
Group G2
Residual Variances
FC1 0.741 0.071 10.438 0.000
FC4 0.273 0.026 10.400 0.000
FC5 0.427 0.045 9.429 0.000
FC6 0.370 0.038 9.666 0.000
FC9 0.165 0.027 6.173 0.000
C112
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
Group G1
Means
CONFLICT 1.843 0.051 36.087 0.000
Intercepts
FC1 0.323 0.115 2.797 0.005
FC4 0.346 0.113 3.062 0.002
FC5 -0.051 0.095 -0.531 0.595
FC6 -0.144 0.097 -1.476 0.140
FC9 -0.474 0.087 -5.427 0.000
Group G2
Means
CONFLICT 1.532 0.039 39.431 0.000
Intercepts
FC1 0.486 0.105 4.641 0.000
FC4 0.202 0.089 2.263 0.024
FC5 -0.051 0.095 -0.531 0.595
FC6 -0.144 0.097 -1.476 0.140
FC9 -0.474 0.087 -5.427 0.000
C113
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
Group G1
Means
CONFLICT 1.843 0.051 36.087 0.000
Variances
CONFLICT 0.412 0.051 8.151 0.000
Group G2
Means
CONFLICT 1.532 0.039 39.431 0.000
Variances
CONFLICT 0.235 0.027 8.759 0.000
C114
1.843 1.532 .311.48
.642.412
1.843 1.532 .311.64
.484.235
C115
full metric
partial scalar (3/5)
error, none tally
C116