Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 11:12 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a discrete-time
survival analysis
DATA: FILE IS ex6.19.dat;
VARIABLE: NAMES ARE u1-u4 x;
CATEGORICAL = u1-u4;
MISSING = ALL (999);
ANALYSIS: ESTIMATOR = MLR;
MODEL: f BY u1-u4@1;
f ON x;
f@0;
INPUT READING TERMINATED NORMALLY
this is an example of a discrete-time
survival analysis
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 500
Number of dependent variables 4
Number of independent variables 1
Number of continuous latent variables 1
Observed dependent variables
Binary and ordered categorical (ordinal)
U1 U2 U3 U4
Observed independent variables
X
Continuous latent variables
F
Estimator MLR
Information matrix OBSERVED
Optimization Specifications for the Quasi-Newton Algorithm for
Continuous Outcomes
Maximum number of iterations 100
Convergence criterion 0.100D-05
Optimization Specifications for the EM Algorithm
Maximum number of iterations 500
Convergence criteria
Loglikelihood change 0.100D-02
Relative loglikelihood change 0.100D-05
Derivative 0.100D-02
Optimization Specifications for the M step of the EM Algorithm for
Categorical Latent variables
Number of M step iterations 1
M step convergence criterion 0.100D-02
Basis for M step termination ITERATION
Optimization Specifications for the M step of the EM Algorithm for
Censored, Binary or Ordered Categorical (Ordinal), Unordered
Categorical (Nominal) and Count Outcomes
Number of M step iterations 1
M step convergence criterion 0.100D-02
Basis for M step termination ITERATION
Maximum value for logit thresholds 15
Minimum value for logit thresholds -15
Minimum expected cell size for chi-square 0.100D-01
Maximum number of iterations for H1 2000
Convergence criterion for H1 0.100D-03
Optimization algorithm EMA
Integration Specifications
Type STANDARD
Number of integration points 15
Dimensions of numerical integration 0
Adaptive quadrature ON
Link LOGIT
Cholesky ON
Input data file(s)
ex6.19.dat
Input data format FREE
SUMMARY OF DATA
Number of missing data patterns 4
Number of y missing data patterns 0
Number of u missing data patterns 4
COVARIANCE COVERAGE OF DATA
Minimum covariance coverage value 0.100
PROPORTION OF DATA PRESENT FOR U
Covariance Coverage
U1 U2 U3 U4
________ ________ ________ ________
U1 1.000
U2 0.870 0.870
U3 0.696 0.696 0.696
U4 0.524 0.524 0.524 0.524
UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES
U1
Category 1 0.870 435.000
Category 2 0.130 65.000
U2
Category 1 0.800 348.000
Category 2 0.200 87.000
U3
Category 1 0.753 262.000
Category 2 0.247 86.000
U4
Category 1 0.702 184.000
Category 2 0.298 78.000
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
X 0.032 0.053 -2.597 0.20% -0.781 -0.277 -0.002
500.000 0.991 -0.272 3.057 0.20% 0.281 0.908
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 5
Loglikelihood
H0 Value -726.559
H0 Scaling Correction Factor 0.9950
for MLR
Information Criteria
Akaike (AIC) 1463.117
Bayesian (BIC) 1484.190
Sample-Size Adjusted BIC 1468.320
(n* = (n + 2) / 24)
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
F BY
U1 1.000 0.000 999.000 999.000
U2 1.000 0.000 999.000 999.000
U3 1.000 0.000 999.000 999.000
U4 1.000 0.000 999.000 999.000
F ON
X 0.597 0.070 8.505 0.000
Thresholds
U1$1 2.047 0.138 14.795 0.000
U2$1 1.455 0.125 11.600 0.000
U3$1 1.106 0.129 8.559 0.000
U4$1 0.762 0.137 5.555 0.000
Residual Variances
F 0.000 0.000 999.000 999.000
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.218E+00
(ratio of smallest to largest eigenvalue)
RESULTS IN PROBABILITY SCALE
Estimate
U1
Category 1 0.870
Category 2 0.130
U2
Category 1 0.792
Category 2 0.208
U3
Category 1 0.733
Category 2 0.267
U4
Category 1 0.666
Category 2 0.334
Beginning Time: 23:12:21
Ending Time: 23:12:21
Elapsed Time: 00:00:00
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