Mplus VERSION 8
MUTHEN & MUTHEN
04/10/2017   4:42 AM

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:  04:42:46
        Ending Time:  04:42:46
       Elapsed Time:  00:00:00



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