Mplus VERSION 7.4
MUTHEN & MUTHEN
01/07/2017 4:59 PM
INPUT INSTRUCTIONS
TITLE: Multilevel SEM_ICC
DATA: FILE = crossroad_couple_web.csv;
VARIABLE:
NAMES = pairid sex length effica irrep subwb;
USEVARIABLES = effica irrep subwb;
MISSING = .;
CLUSTER = pairid;
ANALYSIS:
TYPE = TWOLEVEL;
MODEL:
%WITHIN%
effica(w1);
irrep(w2);
subwb(w3);
%BETWEEN%
effica(b1);
irrep(b2);
subwb(b3);
MODEL CONSTRAINT:
NEW(icc1);
NEW(icc2);
NEW(icc3);
icc1 = b1/(w1+b1);
icc2 = b2/(w2+b2);
icc3 = b3/(w3+b3);
OUTPUT:
SAMPSTAT TECH4;
*** WARNING in MODEL command
Variable is uncorrelated with all other variables: EFFICA
*** WARNING in MODEL command
Variable is uncorrelated with all other variables: IRREP
*** WARNING in MODEL command
Variable is uncorrelated with all other variables: SUBWB
*** WARNING in MODEL command
At least one variable is uncorrelated with all other variables in the
model.
Check that this is what is intended.
4 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS
Multilevel SEM_ICC
SUMMARY OF ANALYSIS
Number of groups
1
Number of observations
194
Number of dependent variables
3
Number of independent variables
0
Number of continuous latent variables
0
Observed dependent variables
Continuous
EFFICA
IRREP
SUBWB
Variables with special functions
Cluster variable PAIRID
Estimator
MLR
Information matrix
OBSERVED
Maximum number of iterations
100
Convergence criterion
0.100D-05
Maximum number of EM iterations
500
Convergence criteria for the EM algorithm
Loglikelihood change
0.100D-02
Relative loglikelihood change
0.100D-05
Derivative
0.100D-03
Minimum variance
0.100D-03
Maximum number of steepest descent
iterations
20
Maximum number of iterations for H1
2000
Convergence criterion for H1
0.100D-03
Optimization algorithm
EMA
Input data file(s)
crossroad_couple_web.csv
Input data format FREE
SUMMARY OF DATA
Number of missing data
patterns
3
Number of
clusters
97
Average cluster
size
2.000
Estimated Intraclass
Correlations for the Y Variables
Intraclass
Intraclass
Intraclass
Variable Correlation Variable Correlation Variable Correlation
EFFICA 0.373 IRREP
0.319
SUBWB
0.251
COVARIANCE COVERAGE OF DATA
Minimum covariance coverage value 0.100
PROPORTION OF DATA
PRESENT
Covariance Coverage
EFFICA
IRREP
SUBWB
________
________
________
EFFICA
0.990
IRREP
0.990
1.000
SUBWB
0.969
0.979
0.979
SAMPLE STATISTICS
NOTE:
The sample statistics for within and between refer to the
maximum-likelihood estimated within and between covariance
matrices,
respectively.
ESTIMATED SAMPLE
STATISTICS FOR WITHIN
Means
EFFICA
IRREP
SUBWB
________
________
________
1
0.000
0.000
0.000
Covariances
EFFICA
IRREP
SUBWB
________
________
________
EFFICA
0.256
IRREP 0.029
0.227
SUBWB
0.045
0.023
0.144
Correlations
EFFICA
IRREP
SUBWB
________
________
________
EFFICA
1.000
IRREP
0.120
1.000
SUBWB
0.234
0.126
1.000
ESTIMATED SAMPLE
STATISTICS FOR BETWEEN
Means
EFFICA
IRREP
SUBWB
________
________
________
1
3.633
4.662 2.889
Covariances
EFFICA
IRREP
SUBWB
________
________
________
EFFICA
0.153
IRREP
0.084
0.106
SUBWB
0.054
0.017
0.048
Correlations
EFFICA
IRREP
SUBWB
________
________
________
EFFICA
1.000
IRREP
0.659
1.000
SUBWB
0.632
0.237
1.000
MAXIMUM LOG-LIKELIHOOD
VALUE FOR THE UNRESTRICTED (H1) MODEL IS -431.427
UNIVARIATE SAMPLE STATISTICS
UNIVARIATE
HIGHER-ORDER MOMENT DESCRIPTIVE STATISTICS
Variable/
Mean/ Skewness/ Minimum/ % with
Percentiles
Sample Size
Variance
Kurtosis
Maximum Min/Max 20%/60% 40%/80% Median
EFFICA
3.636
0.097
1.889 0.52% 3.000 3.444 3.667
192.000 0.409 -0.388 5.000 3.12% 3.778 4.222
IRREP
4.662
-1.886 2.000 0.52% 4.250 5.000 5.000
194.000 0.333 3.239 5.000 63.92% 5.000 5.000
SUBWB
2.891
-0.747 1.250 1.05% 2.583 2.833 2.917
190.000 0.192 1.298 3.833 0.53% 3.000 3.250
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters
9
Loglikelihood
H0 Value
-452.801
H0 Scaling Correction Factor 1.2573
for MLR
H1 Value
-431.427
H1 Scaling Correction Factor 1.1638
for MLR
Information Criteria
Akaike (AIC)
923.601
Bayesian (BIC)
953.012
Sample-Size Adjusted BIC
924.502
(n* = (n + 2) / 24)
Chi-Square Test of Model Fit
Value
41.762*
Degrees of Freedom
6
P-Value
0.0000
Scaling Correction Factor 1.0236
for MLR
* The chi-square value for MLM,
MLMV, MLR, ULSMV, WLSM and WLSMV cannot be used
for chi-square difference
testing in the regular way. MLM,
MLR and WLSM
chi-square difference
testing is described on the Mplus website.
MLMV, WLSMV,
and ULSMV difference testing
is done using the DIFFTEST option.
RMSEA (Root Mean Square Error Of
Approximation)
Estimate
0.175
CFI/TLI
CFI
0.000
TLI
-0.001
Chi-Square Test of Model Fit for the
Baseline Model
Value
41.718
Degrees of Freedom
6
P-Value
0.0000
SRMR (Standardized Root Mean Square
Residual)
Value for Within
0.119
Value for Between
0.385
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
Within Level
Variances
EFFICA
0.258
0.031
8.206
0.000
IRREP
0.227
0.047
4.857
0.000
SUBWB
0.144
0.025
5.828
0.000
Between Level
Means
EFFICA
3.634
0.054
67.413
0.000
IRREP
4.662
0.048
98.023
0.000
SUBWB
2.890
0.035
81.714
0.000
Variances
EFFICA
0.151
0.039 3.882 0.000
IRREP
0.106
0.048
2.206
0.027
SUBWB
0.048
0.017
2.800
0.005
New/Additional Parameters
ICC1
0.369
0.077
4.794
0.000
ICC2
0.317
0.115
2.751
0.006
ICC3
0.248
0.083
2.969
0.003
QUALITY OF NUMERICAL RESULTS
Condition Number for
the Information Matrix
0.133E-03
(ratio of
smallest to largest eigenvalue)
TECHNICAL 4 OUTPUT
DIAGRAM INFORMATION
Mplus diagrams are currently not available for multilevel analysis.
No diagram output was produced.
Beginning Time: 16:59:24
Ending Time: 16:59:24
Elapsed
Time: 00:00:00
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