Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 11:12 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a continuous-time
survival analysis using a parametric
proportional hazard model
DATA: FILE = ex6.21.dat;
VARIABLE: NAMES = t x tc;
SURVIVAL = t(20*1);
TIMECENSORED = tc (0 = NOT 1 = RIGHT);
ANALYSIS: BASEHAZARD = ON;
MODEL: [t#1-t#21];
t ON x;
INPUT READING TERMINATED NORMALLY
this is an example of a continuous-time
survival analysis using a parametric
proportional hazard model
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 500
Number of dependent variables 1
Number of independent variables 1
Number of continuous latent variables 0
Observed dependent variables
Time-to-event (survival)
Parametric (time intervals)
T (20)
Observed independent variables
X
Variables with special functions
Time-censoring variables
TC
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
Optimization algorithm EMA
Integration Specifications
Type STANDARD
Number of integration points 15
Dimensions of numerical integration 0
Adaptive quadrature ON
Base Hazard ON
Cholesky OFF
Input data file(s)
ex6.21.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
X -0.034 0.041 -2.941 0.20% -0.847 -0.321 -0.066
500.000 1.021 -0.025 3.033 0.20% 0.198 0.838
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 22
Loglikelihood
H0 Value -1037.276
H0 Scaling Correction Factor 0.9972
for MLR
Information Criteria
Akaike (AIC) 2118.552
Bayesian (BIC) 2211.273
Sample-Size Adjusted BIC 2141.444
(n* = (n + 2) / 24)
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
T ON
X 0.090 0.063 1.435 0.151
Base Hazard Parameters
T#1 0.046 0.010 4.704 0.000
T#2 0.045 0.010 4.479 0.000
T#3 0.058 0.012 4.791 0.000
T#4 0.042 0.011 3.881 0.000
T#5 0.037 0.011 3.453 0.001
T#6 0.062 0.015 4.219 0.000
T#7 0.061 0.015 4.008 0.000
T#8 0.060 0.016 3.767 0.000
T#9 0.061 0.017 3.616 0.000
T#10 0.047 0.016 2.979 0.003
T#11 0.069 0.020 3.426 0.001
T#12 0.063 0.020 3.159 0.002
T#13 0.056 0.020 2.822 0.005
T#14 0.061 0.021 2.851 0.004
T#15 0.060 0.023 2.640 0.008
T#16 0.039 0.020 1.996 0.046
T#17 0.044 0.022 2.026 0.043
T#18 0.063 0.028 2.232 0.026
T#19 0.055 0.027 2.006 0.045
T#20 0.091 0.037 2.478 0.013
T#21 0.044 0.007 5.882 0.000
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.145E-01
(ratio of smallest to largest eigenvalue)
Beginning Time: 23:12:25
Ending Time: 23:12:25
Elapsed Time: 00:00:00
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