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 categorical outcome
DATA: FILE IS ex6.4.dat;
VARIABLE: NAMES ARE u11-u14;
CATEGORICAL ARE u11-u14;
MODEL: i s | u11@0 u12@1 u13@2 u14@3;
INPUT READING TERMINATED NORMALLY
this is an example of a linear growth
model for a categorical 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 2
Observed dependent variables
Binary and ordered categorical (ordinal)
U11 U12 U13 U14
Continuous latent variables
I S
Estimator WLSMV
Maximum number of iterations 1000
Convergence criterion 0.500D-04
Maximum number of steepest descent iterations 20
Parameterization DELTA
Link PROBIT
Input data file(s)
ex6.4.dat
Input data format FREE
UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES
U11
Category 1 0.310 155.000
Category 2 0.690 345.000
U12
Category 1 0.466 233.000
Category 2 0.534 267.000
U13
Category 1 0.624 312.000
Category 2 0.376 188.000
U14
Category 1 0.714 357.000
Category 2 0.286 143.000
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 8
Chi-Square Test of Model Fit
Value 1.214*
Degrees of Freedom 2
P-Value 0.5449
* 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 0.000
90 Percent C.I. 0.000 0.077
Probability RMSEA <= .05 0.819
CFI/TLI
CFI 1.000
TLI 1.000
Chi-Square Test of Model Fit for the Baseline Model
Value 296.848
Degrees of Freedom 6
P-Value 0.0000
SRMR (Standardized Root Mean Square Residual)
Value 0.016
Optimum Function Value for Weighted Least-Squares Estimator
Value 0.78968175D-03
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
I |
U11 1.000 0.000 999.000 999.000
U12 1.000 0.000 999.000 999.000
U13 1.000 0.000 999.000 999.000
U14 1.000 0.000 999.000 999.000
S |
U11 0.000 0.000 999.000 999.000
U12 1.000 0.000 999.000 999.000
U13 2.000 0.000 999.000 999.000
U14 3.000 0.000 999.000 999.000
S WITH
I -0.007 0.054 -0.132 0.895
Means
I 0.000 0.000 999.000 999.000
S -0.407 0.053 -7.680 0.000
Thresholds
U11$1 -0.494 0.058 -8.503 0.000
U12$1 -0.494 0.058 -8.503 0.000
U13$1 -0.494 0.058 -8.503 0.000
U14$1 -0.494 0.058 -8.503 0.000
Variances
I 0.439 0.114 3.845 0.000
S 0.042 0.035 1.202 0.229
Scales
U11 1.000 0.000 999.000 999.000
U12 1.060 0.149 7.133 0.000
U13 1.012 0.192 5.259 0.000
U14 0.772 0.153 5.029 0.000
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.496E-03
(ratio of smallest to largest eigenvalue)
R-SQUARE
Observed Residual
Variable Estimate Variance
U11 0.439 0.561
U12 0.524 0.424
U13 0.592 0.399
U14 0.461 0.904
Beginning Time: 23:12:50
Ending Time: 23:12:50
Elapsed Time: 00:00:00
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