Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 11:12 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a piecewise growth
model for a continuous outcome
DATA: FILE IS ex6.11.dat;
VARIABLE: NAMES ARE y1-y5;
MODEL: i s1 | y1@0 y2@1 y3@2 y4@2 y5@2;
i s2 | y1@0 y2@0 y3@0 y4@1 y5@2;
INPUT READING TERMINATED NORMALLY
this is an example of a piecewise growth
model for a continuous outcome
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 500
Number of dependent variables 5
Number of independent variables 0
Number of continuous latent variables 3
Observed dependent variables
Continuous
Y1 Y2 Y3 Y4 Y5
Continuous latent variables
I S1 S2
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)
ex6.11.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
Y1 0.443 0.035 -2.639 0.20% -0.566 0.132 0.373
500.000 1.367 -0.359 3.613 0.20% 0.725 1.483
Y2 1.584 0.070 -2.277 0.20% 0.509 1.213 1.520
500.000 1.732 -0.150 5.758 0.20% 1.895 2.748
Y3 2.595 0.027 -1.458 0.20% 1.188 2.200 2.583
500.000 2.318 -0.225 7.146 0.20% 2.999 3.956
Y4 4.535 -0.045 -0.255 0.20% 3.272 4.051 4.462
500.000 2.491 -0.004 9.106 0.20% 4.827 5.904
Y5 6.535 0.026 1.538 0.20% 5.000 6.175 6.626
500.000 3.269 0.182 12.294 0.20% 7.042 7.931
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 14
Loglikelihood
H0 Value -3706.171
H1 Value -3703.549
Information Criteria
Akaike (AIC) 7440.342
Bayesian (BIC) 7499.346
Sample-Size Adjusted BIC 7454.909
(n* = (n + 2) / 24)
Chi-Square Test of Model Fit
Value 5.244
Degrees of Freedom 6
P-Value 0.5130
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000
90 Percent C.I. 0.000 0.054
Probability RMSEA <= .05 0.929
CFI/TLI
CFI 1.000
TLI 1.000
Chi-Square Test of Model Fit for the Baseline Model
Value 1587.697
Degrees of Freedom 10
P-Value 0.0000
SRMR (Standardized Root Mean Square Residual)
Value 0.010
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
I |
Y1 1.000 0.000 999.000 999.000
Y2 1.000 0.000 999.000 999.000
Y3 1.000 0.000 999.000 999.000
Y4 1.000 0.000 999.000 999.000
Y5 1.000 0.000 999.000 999.000
S1 |
Y1 0.000 0.000 999.000 999.000
Y2 1.000 0.000 999.000 999.000
Y3 2.000 0.000 999.000 999.000
Y4 2.000 0.000 999.000 999.000
Y5 2.000 0.000 999.000 999.000
S2 |
Y1 0.000 0.000 999.000 999.000
Y2 0.000 0.000 999.000 999.000
Y3 0.000 0.000 999.000 999.000
Y4 1.000 0.000 999.000 999.000
Y5 2.000 0.000 999.000 999.000
S1 WITH
I -0.029 0.049 -0.589 0.556
S2 WITH
I 0.059 0.036 1.642 0.101
S1 -0.031 0.026 -1.184 0.237
Means
I 0.462 0.052 8.955 0.000
S1 1.071 0.030 35.945 0.000
S2 1.957 0.030 64.314 0.000
Intercepts
Y1 0.000 0.000 999.000 999.000
Y2 0.000 0.000 999.000 999.000
Y3 0.000 0.000 999.000 999.000
Y4 0.000 0.000 999.000 999.000
Y5 0.000 0.000 999.000 999.000
Variances
I 0.985 0.100 9.827 0.000
S1 0.240 0.037 6.408 0.000
S2 0.219 0.042 5.265 0.000
Residual Variances
Y1 0.394 0.077 5.156 0.000
Y2 0.525 0.043 12.185 0.000
Y3 0.501 0.068 7.354 0.000
Y4 0.483 0.048 10.089 0.000
Y5 0.559 0.103 5.424 0.000
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.136E-01
(ratio of smallest to largest eigenvalue)
Beginning Time: 23:12:16
Ending Time: 23:12:16
Elapsed Time: 00:00:00
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