Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 11:09 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a path analysis
with categorical dependent variables using
the Theta parameterization
DATA: FILE IS ex3.13.dat;
VARIABLE: NAMES ARE u1-u3 x1-x3;
CATEGORICAL ARE u1-u3;
ANALYSIS: PARAMETERIZATION = THETA;
MODEL: u1 u2 ON x1 x2 x3;
u3 ON u1 u2 x2;
INPUT READING TERMINATED NORMALLY
this is an example of a path analysis
with categorical dependent variables using
the Theta parameterization
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 1000
Number of dependent variables 3
Number of independent variables 3
Number of continuous latent variables 0
Observed dependent variables
Binary and ordered categorical (ordinal)
U1 U2 U3
Observed independent variables
X1 X2 X3
Estimator WLSMV
Maximum number of iterations 1000
Convergence criterion 0.500D-04
Maximum number of steepest descent iterations 20
Parameterization THETA
Link PROBIT
Input data file(s)
ex3.13.dat
Input data format FREE
UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES
U1
Category 1 0.420 420.000
Category 2 0.207 207.000
Category 3 0.373 373.000
U2
Category 1 0.544 544.000
Category 2 0.456 456.000
U3
Category 1 0.434 434.000
Category 2 0.110 110.000
Category 3 0.101 101.000
Category 4 0.355 355.000
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
X1 0.004 0.016 -3.519 0.10% -0.883 -0.223 -0.003
1000.000 1.078 0.179 3.468 0.10% 0.248 0.838
X2 -0.014 -0.058 -3.639 0.10% -0.895 -0.236 0.040
1000.000 1.047 -0.113 2.993 0.10% 0.274 0.825
X3 -0.030 0.163 -3.238 0.10% -0.895 -0.313 -0.053
1000.000 1.064 0.241 4.046 0.10% 0.165 0.814
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 15
Chi-Square Test of Model Fit
Value 6.871*
Degrees of Freedom 3
P-Value 0.0761
* 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 0.036
90 Percent C.I. 0.000 0.072
Probability RMSEA <= .05 0.691
CFI/TLI
CFI 0.998
TLI 0.991
Chi-Square Test of Model Fit for the Baseline Model
Value 1810.771
Degrees of Freedom 12
P-Value 0.0000
SRMR (Standardized Root Mean Square Residual)
Value 0.019
Optimum Function Value for Weighted Least-Squares Estimator
Value 0.33719784D-02
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
U1 ON
X1 2.917 0.152 19.148 0.000
X2 1.926 0.103 18.655 0.000
X3 1.030 0.077 13.461 0.000
U2 ON
X1 1.046 0.105 9.933 0.000
X2 2.084 0.175 11.908 0.000
X3 3.213 0.230 13.984 0.000
U3 ON
U1 1.110 0.184 6.023 0.000
U2 -1.027 0.196 -5.248 0.000
X2 2.188 0.324 6.757 0.000
Thresholds
U1$1 -0.957 0.081 -11.783 0.000
U1$2 1.109 0.087 12.761 0.000
U2$1 0.064 0.080 0.806 0.420
U3$1 -0.653 0.127 -5.135 0.000
U3$2 0.523 0.124 4.219 0.000
U3$3 1.593 0.225 7.068 0.000
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.172E-02
(ratio of smallest to largest eigenvalue)
Beginning Time: 23:09:15
Ending Time: 23:09:15
Elapsed Time: 00:00:00
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