Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 10:24 PM
INPUT INSTRUCTIONS
title: this is an example of a linear growth
model for a continuous outcome
montecarlo:
names = y11-y14;
nobs = 500;
nreps = 1;
save = ex6.1.dat;
model population:
i s | y11@0 y12@1 y13@2 y14@3;
[y11-y14@0]; ! this is actually default in MC
y11-y14*.5;
[i*.5 s*1];
i*1; s*.2; i with s*.1;
model:
i s | y11@0 y12@1 y13@2 y14@3;
y11-y14*.5;
[i*.5 s*1];
i*1; s*.2; i with s*.1;
output:
tech9;
INPUT READING TERMINATED NORMALLY
this is an example of a linear growth
model for a continuous outcome
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 500
Number of replications
Requested 1
Completed 1
Value of seed 0
Number of dependent variables 4
Number of independent variables 0
Number of continuous latent variables 2
Observed dependent variables
Continuous
Y11 Y12 Y13 Y14
Continuous latent variables
I S
Estimator ML
Information matrix OBSERVED
Maximum number of iterations 1000
Convergence criterion 0.500D-04
Maximum number of steepest descent iterations 20
SAMPLE STATISTICS FOR THE FIRST REPLICATION
SAMPLE STATISTICS
Means
Y11 Y12 Y13 Y14
________ ________ ________ ________
0.514 1.566 2.568 3.601
Covariances
Y11 Y12 Y13 Y14
________ ________ ________ ________
Y11 1.449
Y12 1.131 1.974
Y13 1.224 1.866 2.931
Y14 1.389 2.161 3.013 4.298
Correlations
Y11 Y12 Y13 Y14
________ ________ ________ ________
Y11 1.000
Y12 0.668 1.000
Y13 0.594 0.776 1.000
Y14 0.557 0.742 0.849 1.000
MODEL FIT INFORMATION
Number of Free Parameters 9
Loglikelihood
H0 Value
Mean -3016.386
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 -3016.386 -3016.386
0.980 0.000 -3016.386 -3016.386
0.950 0.000 -3016.386 -3016.386
0.900 0.000 -3016.386 -3016.386
0.800 0.000 -3016.386 -3016.386
0.700 0.000 -3016.386 -3016.386
0.500 0.000 -3016.386 -3016.386
0.300 0.000 -3016.386 -3016.386
0.200 0.000 -3016.386 -3016.386
0.100 0.000 -3016.386 -3016.386
0.050 0.000 -3016.386 -3016.386
0.020 0.000 -3016.386 -3016.386
0.010 0.000 -3016.386 -3016.386
H1 Value
Mean -3014.089
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 -3014.089 -3014.089
0.980 0.000 -3014.089 -3014.089
0.950 0.000 -3014.089 -3014.089
0.900 0.000 -3014.089 -3014.089
0.800 0.000 -3014.089 -3014.089
0.700 0.000 -3014.089 -3014.089
0.500 0.000 -3014.089 -3014.089
0.300 0.000 -3014.089 -3014.089
0.200 0.000 -3014.089 -3014.089
0.100 0.000 -3014.089 -3014.089
0.050 0.000 -3014.089 -3014.089
0.020 0.000 -3014.089 -3014.089
0.010 0.000 -3014.089 -3014.089
Information Criteria
Akaike (AIC)
Mean 6050.772
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 6050.772 6050.772
0.980 0.000 6050.772 6050.772
0.950 0.000 6050.772 6050.772
0.900 0.000 6050.772 6050.772
0.800 0.000 6050.772 6050.772
0.700 0.000 6050.772 6050.772
0.500 0.000 6050.772 6050.772
0.300 0.000 6050.772 6050.772
0.200 0.000 6050.772 6050.772
0.100 0.000 6050.772 6050.772
0.050 0.000 6050.772 6050.772
0.020 0.000 6050.772 6050.772
0.010 0.000 6050.772 6050.772
Bayesian (BIC)
Mean 6088.703
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 6088.703 6088.703
0.980 0.000 6088.703 6088.703
0.950 0.000 6088.703 6088.703
0.900 0.000 6088.703 6088.703
0.800 0.000 6088.703 6088.703
0.700 0.000 6088.703 6088.703
0.500 0.000 6088.703 6088.703
0.300 0.000 6088.703 6088.703
0.200 0.000 6088.703 6088.703
0.100 0.000 6088.703 6088.703
0.050 0.000 6088.703 6088.703
0.020 0.000 6088.703 6088.703
0.010 0.000 6088.703 6088.703
Sample-Size Adjusted BIC (n* = (n + 2) / 24)
Mean 6060.137
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 6060.137 6060.137
0.980 0.000 6060.137 6060.137
0.950 0.000 6060.137 6060.137
0.900 0.000 6060.137 6060.137
0.800 0.000 6060.137 6060.137
0.700 0.000 6060.137 6060.137
0.500 0.000 6060.137 6060.137
0.300 0.000 6060.137 6060.137
0.200 0.000 6060.137 6060.137
0.100 0.000 6060.137 6060.137
0.050 0.000 6060.137 6060.137
0.020 0.000 6060.137 6060.137
0.010 0.000 6060.137 6060.137
Chi-Square Test of Model Fit
Degrees of freedom 5
Mean 4.593
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 1.000 0.554 4.593
0.980 1.000 0.752 4.593
0.950 1.000 1.145 4.593
0.900 1.000 1.610 4.593
0.800 1.000 2.343 4.593
0.700 1.000 3.000 4.593
0.500 1.000 4.351 4.593
0.300 0.000 6.064 4.593
0.200 0.000 7.289 4.593
0.100 0.000 9.236 4.593
0.050 0.000 11.070 4.593
0.020 0.000 13.388 4.593
0.010 0.000 15.086 4.593
RMSEA (Root Mean Square Error Of Approximation)
Mean 0.000
Std Dev 0.000
Number of successful computations 1
Cumulative Distribution Function
Value Function Value
0.990 1.000
0.980 1.000
0.950 1.000
0.900 1.000
0.800 1.000
0.700 1.000
0.500 1.000
0.300 1.000
0.200 1.000
0.100 1.000
0.050 1.000
0.020 1.000
0.010 1.000
CFI/TLI
CFI
Mean 1.000
Std Dev 0.000
Number of successful computations 1
Cumulative Distribution Function
Value Function Value
0.990 0.000
0.980 0.000
0.950 0.000
0.900 0.000
0.800 0.000
0.700 0.000
0.500 0.000
0.300 0.000
0.200 0.000
0.100 0.000
0.050 0.000
0.020 0.000
0.010 0.000
TLI
Mean 1.000
Std Dev 0.000
Number of successful computations 1
Cumulative Distribution Function
Value Function Value
0.990 0.000
0.980 0.000
0.950 0.000
0.900 0.000
0.800 0.000
0.700 0.000
0.500 0.000
0.300 0.000
0.200 0.000
0.100 0.000
0.050 0.000
0.020 0.000
0.010 0.000
SRMR (Standardized Root Mean Square Residual)
Mean 0.010
Std Dev 0.000
Number of successful computations 1
Cumulative Distribution Function
Value Function Value
0.990 1.000
0.980 1.000
0.950 1.000
0.900 1.000
0.800 1.000
0.700 1.000
0.500 1.000
0.300 1.000
0.200 1.000
0.100 1.000
0.050 1.000
0.020 1.000
0.010 1.000
MODEL RESULTS
ESTIMATES S. E. M. S. E. 95% % Sig
Population Average Std. Dev. Average Cover Coeff
I |
Y11 1.000 1.0000 0.0000 0.0000 0.0000 1.000 0.000
Y12 1.000 1.0000 0.0000 0.0000 0.0000 1.000 0.000
Y13 1.000 1.0000 0.0000 0.0000 0.0000 1.000 0.000
Y14 1.000 1.0000 0.0000 0.0000 0.0000 1.000 0.000
S |
Y11 0.000 0.0000 0.0000 0.0000 0.0000 1.000 0.000
Y12 1.000 1.0000 0.0000 0.0000 0.0000 1.000 0.000
Y13 2.000 2.0000 0.0000 0.0000 0.0000 1.000 0.000
Y14 3.000 3.0000 0.0000 0.0000 0.0000 1.000 0.000
I WITH
S 0.100 0.1329 0.0000 0.0324 0.0011 1.000 1.000
Means
I 0.500 0.5227 0.0000 0.0515 0.0005 1.000 1.000
S 1.000 1.0263 0.0000 0.0255 0.0007 1.000 1.000
Intercepts
Y11 0.000 0.0000 0.0000 0.0000 0.0000 1.000 0.000
Y12 0.000 0.0000 0.0000 0.0000 0.0000 1.000 0.000
Y13 0.000 0.0000 0.0000 0.0000 0.0000 1.000 0.000
Y14 0.000 0.0000 0.0000 0.0000 0.0000 1.000 0.000
Variances
I 1.000 0.9889 0.0000 0.0885 0.0001 1.000 1.000
S 0.200 0.2238 0.0000 0.0222 0.0006 1.000 1.000
Residual Variances
Y11 0.500 0.4747 0.0000 0.0584 0.0006 1.000 1.000
Y12 0.500 0.4821 0.0000 0.0402 0.0003 1.000 1.000
Y13 0.500 0.4732 0.0000 0.0469 0.0007 1.000 1.000
Y14 0.500 0.5447 0.0000 0.0826 0.0020 1.000 1.000
QUALITY OF NUMERICAL RESULTS
Average Condition Number for the Information Matrix 0.462E-01
(ratio of smallest to largest eigenvalue)
TECHNICAL OUTPUT
PARAMETER SPECIFICATION
NU
Y11 Y12 Y13 Y14
________ ________ ________ ________
0 0 0 0
LAMBDA
I S
________ ________
Y11 0 0
Y12 0 0
Y13 0 0
Y14 0 0
THETA
Y11 Y12 Y13 Y14
________ ________ ________ ________
Y11 1
Y12 0 2
Y13 0 0 3
Y14 0 0 0 4
ALPHA
I S
________ ________
5 6
BETA
I S
________ ________
I 0 0
S 0 0
PSI
I S
________ ________
I 7
S 8 9
STARTING VALUES
NU
Y11 Y12 Y13 Y14
________ ________ ________ ________
0.000 0.000 0.000 0.000
LAMBDA
I S
________ ________
Y11 1.000 0.000
Y12 1.000 1.000
Y13 1.000 2.000
Y14 1.000 3.000
THETA
Y11 Y12 Y13 Y14
________ ________ ________ ________
Y11 0.500
Y12 0.000 0.500
Y13 0.000 0.000 0.500
Y14 0.000 0.000 0.000 0.500
ALPHA
I S
________ ________
0.500 1.000
BETA
I S
________ ________
I 0.000 0.000
S 0.000 0.000
PSI
I S
________ ________
I 1.000
S 0.100 0.200
POPULATION VALUES
NU
Y11 Y12 Y13 Y14
________ ________ ________ ________
0.000 0.000 0.000 0.000
LAMBDA
I S
________ ________
Y11 1.000 0.000
Y12 1.000 1.000
Y13 1.000 2.000
Y14 1.000 3.000
THETA
Y11 Y12 Y13 Y14
________ ________ ________ ________
Y11 0.500
Y12 0.000 0.500
Y13 0.000 0.000 0.500
Y14 0.000 0.000 0.000 0.500
ALPHA
I S
________ ________
0.500 1.000
BETA
I S
________ ________
I 0.000 0.000
S 0.000 0.000
PSI
I S
________ ________
I 1.000
S 0.100 0.200
TECHNICAL 9 OUTPUT
Error messages for each replication (if any)
SAVEDATA INFORMATION
Order of variables
Y11
Y12
Y13
Y14
Save file
ex6.1.dat
Save file format Free
Save file record length 10000
Beginning Time: 22:24:13
Ending Time: 22:24:14
Elapsed Time: 00:00:01
MUTHEN & MUTHEN
3463 Stoner Ave.
Los Angeles, CA 90066
Tel: (310) 391-9971
Fax: (310) 391-8971
Web: www.StatModel.com
Support: Support@StatModel.com
Copyright (c) 1998-2022 Muthen & Muthen
Back to examples