Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 11:12 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a quadratic growth
model for a continuous outcome
DATA: FILE IS ex6.9.dat;
VARIABLE: NAMES ARE y11-y14;
MODEL: i s q | y11@0 y12@1 y13@2 y14@3;
INPUT READING TERMINATED NORMALLY
this is an example of a quadratic growth
model for a continuous outcome
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 500
Number of dependent variables 4
Number of independent variables 0
Number of continuous latent variables 3
Observed dependent variables
Continuous
Y11 Y12 Y13 Y14
Continuous latent variables
I S Q
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)
ex6.9.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 0.516 -0.170 -3.187 0.20% -0.647 0.196 0.567
500.000 1.932 -0.354 4.077 0.20% 0.861 1.782
Y12 2.088 -0.083 -4.249 0.20% 0.832 1.749 2.083
500.000 2.906 0.208 7.613 0.20% 2.393 3.514
Y13 4.618 -0.009 -3.557 0.20% 2.219 3.734 4.382
500.000 7.944 -0.246 14.280 0.20% 5.371 7.249
Y14 8.240 -0.091 -6.178 0.20% 4.000 6.828 8.194
500.000 24.897 -0.253 22.451 0.20% 9.752 12.656
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 13
Loglikelihood
H0 Value -3975.519
H1 Value -3975.281
Information Criteria
Akaike (AIC) 7977.038
Bayesian (BIC) 8031.828
Sample-Size Adjusted BIC 7990.565
(n* = (n + 2) / 24)
Chi-Square Test of Model Fit
Value 0.475
Degrees of Freedom 1
P-Value 0.4905
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000
90 Percent C.I. 0.000 0.104
Probability RMSEA <= .05 0.701
CFI/TLI
CFI 1.000
TLI 1.000
Chi-Square Test of Model Fit for the Baseline Model
Value 1231.275
Degrees of Freedom 6
P-Value 0.0000
SRMR (Standardized Root Mean Square Residual)
Value 0.004
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
Q |
Y11 0.000 0.000 999.000 999.000
Y12 1.000 0.000 999.000 999.000
Y13 4.000 0.000 999.000 999.000
Y14 9.000 0.000 999.000 999.000
S WITH
I -0.173 0.300 -0.578 0.564
Q WITH
I 0.101 0.080 1.269 0.204
S -0.179 0.117 -1.524 0.127
Means
I 0.521 0.062 8.442 0.000
S 1.035 0.077 13.455 0.000
Q 0.512 0.031 16.441 0.000
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
Variances
I 1.246 0.273 4.569 0.000
S 0.998 0.358 2.787 0.005
Q 0.282 0.060 4.666 0.000
Residual Variances
Y11 0.685 0.265 2.589 0.010
Y12 0.882 0.115 7.705 0.000
Y13 0.946 0.183 5.178 0.000
Y14 0.738 0.945 0.781 0.435
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.241E-03
(ratio of smallest to largest eigenvalue)
Beginning Time: 23:12:54
Ending Time: 23:12:54
Elapsed Time: 00:00:00
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