Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 11:12 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a linear growth
model for a continuous outcome with time-
invariant and time-varying covariates
DATA: FILE IS ex6.10.dat;
VARIABLE: NAMES ARE y11-y14 x1 x2 a31-a34;
MODEL: i s | y11@0 y12@1 y13@2 y14@3;
i s ON x1 x2;
y11 ON a31;
y12 ON a32;
y13 ON a33;
y14 ON a34;
INPUT READING TERMINATED NORMALLY
this is an example of a linear growth
model for a continuous outcome with time-
invariant and time-varying covariates
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 500
Number of dependent variables 4
Number of independent variables 6
Number of continuous latent variables 2
Observed dependent variables
Continuous
Y11 Y12 Y13 Y14
Observed independent variables
X1 X2 A31 A32 A33 A34
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
Input data file(s)
ex6.10.dat
Input data format FREE
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
Y11 0.607 -0.100 -4.515 0.20% -0.545 0.196 0.550
500.000 2.392 0.156 4.417 0.20% 0.978 1.863
Y12 1.695 -0.027 -4.760 0.20% -0.146 1.233 1.701
500.000 4.371 -0.244 7.307 0.20% 2.279 3.419
Y13 2.717 0.082 -6.275 0.20% 0.398 2.064 2.727
500.000 7.045 -0.054 10.187 0.20% 3.373 4.751
Y14 3.759 0.069 -7.203 0.20% 1.188 2.864 3.706
500.000 10.026 -0.021 12.686 0.20% 4.464 6.257
X1 -0.073 0.041 -2.518 0.20% -0.928 -0.356 -0.050
500.000 0.990 -0.354 2.797 0.20% 0.175 0.743
X2 0.127 0.256 -2.012 0.20% -0.657 -0.155 0.061
500.000 0.945 -0.004 3.176 0.20% 0.300 0.938
A31 0.030 -0.123 -2.576 0.20% -0.706 -0.242 -0.011
500.000 0.909 -0.351 2.704 0.20% 0.300 0.899
A32 -0.058 -0.095 -3.990 0.20% -0.880 -0.356 -0.096
500.000 1.026 0.184 2.766 0.20% 0.212 0.828
A33 0.037 0.007 -2.799 0.20% -0.799 -0.217 0.053
500.000 0.961 0.120 3.446 0.20% 0.295 0.856
A34 -0.036 -0.067 -2.736 0.20% -0.872 -0.279 -0.064
500.000 0.928 -0.266 2.542 0.20% 0.243 0.784
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 17
Loglikelihood
H0 Value -3070.619
H1 Value -3057.726
Information Criteria
Akaike (AIC) 6175.239
Bayesian (BIC) 6246.887
Sample-Size Adjusted BIC 6192.928
(n* = (n + 2) / 24)
Chi-Square Test of Model Fit
Value 25.786
Degrees of Freedom 21
P-Value 0.2147
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.021
90 Percent C.I. 0.000 0.046
Probability RMSEA <= .05 0.978
CFI/TLI
CFI 0.998
TLI 0.998
Chi-Square Test of Model Fit for the Baseline Model
Value 2862.582
Degrees of Freedom 30
P-Value 0.0000
SRMR (Standardized Root Mean Square Residual)
Value 0.017
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
I |
Y11 1.000 0.000 999.000 999.000
Y12 1.000 0.000 999.000 999.000
Y13 1.000 0.000 999.000 999.000
Y14 1.000 0.000 999.000 999.000
S |
Y11 0.000 0.000 999.000 999.000
Y12 1.000 0.000 999.000 999.000
Y13 2.000 0.000 999.000 999.000
Y14 3.000 0.000 999.000 999.000
I ON
X1 0.557 0.054 10.278 0.000
X2 0.718 0.055 12.950 0.000
S ON
X1 0.264 0.025 10.543 0.000
X2 0.473 0.026 18.401 0.000
Y11 ON
A31 0.190 0.044 4.294 0.000
Y12 ON
A32 0.323 0.038 8.429 0.000
Y13 ON
A33 0.344 0.038 8.985 0.000
Y14 ON
A34 0.303 0.050 6.002 0.000
S WITH
I 0.055 0.035 1.570 0.117
Intercepts
Y11 0.000 0.000 999.000 999.000
Y12 0.000 0.000 999.000 999.000
Y13 0.000 0.000 999.000 999.000
Y14 0.000 0.000 999.000 999.000
I 0.570 0.054 10.465 0.000
S 1.010 0.025 40.075 0.000
Residual Variances
Y11 0.509 0.068 7.474 0.000
Y12 0.597 0.049 12.268 0.000
Y13 0.481 0.050 9.703 0.000
Y14 0.579 0.089 6.492 0.000
I 1.074 0.097 11.122 0.000
S 0.201 0.022 9.001 0.000
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.307E-01
(ratio of smallest to largest eigenvalue)
Beginning Time: 23:12:15
Ending Time: 23:12:16
Elapsed Time: 00:00:01
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