Mplus VERSION 7.3
MUTHEN & MUTHEN
09/22/2014   6:01 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a two-level
  		continuous-time survival analysis using
  		Cox regression with a random intercept
  DATA:	FILE = ex9.18.dat;
  VARIABLE:	NAMES = t x w tc clus;
  	CLUSTER = clus;
  	WITHIN = x;
  	BETWEEN = w;
  	SURVIVAL = t (ALL);
  	TIMECENSORED = tc (0 = NOT 1 = RIGHT);
  ANALYSIS:	TYPE = TWOLEVEL;
  	BASEHAZARD = OFF;
  MODEL:	%WITHIN%
  	t ON x;
  	%BETWEEN%
  	t ON w;
  	t;



INPUT READING TERMINATED NORMALLY



this is an example of a two-level
continuous-time survival analysis using
Cox regression with a random intercept

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        1000

Number of dependent variables                                    1
Number of independent variables                                  2
Number of continuous latent variables                            0

Observed dependent variables

  Time-to-event (survival)

    Non-parametric
     T

Observed independent variables
   X           W

Variables with special functions

  Cluster variable      CLUS

  Time-censoring variables
   TC

  Within variables
   X

  Between variables
   W


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                            1
  Adaptive quadrature                                           ON
Base Hazard                                                    OFF
Cholesky                                                        ON

Input data file(s)
  ex9.18.dat
Input data format  FREE


SUMMARY OF DATA

     Number of clusters                        110




THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                        3

Loglikelihood

          H0 Value                         116.945
          H0 Scaling Correction Factor      1.0042
            for MLR

Information Criteria

          Akaike (AIC)                    -227.890
          Bayesian (BIC)                  -213.167
          Sample-Size Adjusted BIC        -222.695
            (n* = (n + 2) / 24)



MODEL RESULTS

                                                    Two-Tailed
                    Estimate       S.E.  Est./S.E.    P-Value

Within Level

 T          ON
    X                  0.422      0.043      9.819      0.000

Between Level

 T          ON
    W                  0.203      0.078      2.604      0.009

 Residual Variances
    T                  0.497      0.103      4.801      0.000


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.310E+00
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  18:01:13
        Ending Time:  18:01:13
       Elapsed Time:  00:00:00



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