Mplus VERSION 7.2
MUTHEN & MUTHEN
05/07/2014   2:42 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of continuous-time survival
  		analysis using a Cox regression model to
  		estimate a treatment effect
  DATA:		FILE = ex7.30.dat;
  VARIABLE:	NAMES are t u x tcent class;
  		USEVARIABLES = t-tcent;
  		SURVIVAL = t;
  		TIMECENSORED = tcent;
  		CATEGORICAL = u;
  		CLASSES = c (2);
  ANALYSIS:	TYPE = MIXTURE;
  MODEL:
  		%OVERALL%
  		t ON x;
  		%c#1%
  		[u$1@15];
  		[t@0];
  		%c#2%
  		[u$1@-15];
  		[t];
  OUTPUT:	TECH1 LOGRANK;
  PLOT:		TYPE = PLOT2;



INPUT READING TERMINATED NORMALLY



this is an example of continuous-time survival
analysis using a Cox regression model to
estimate a treatment effect

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                         500

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

Observed dependent variables

  Binary and ordered categorical (ordinal)
   U

  Time-to-event (survival)

    Non-parametric
     T

Observed independent variables
   X

Categorical latent variables
   C

Variables with special functions

  Time-censoring variables
   TCENT


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-06
    Relative loglikelihood change                        0.100D-06
    Derivative                                           0.100D-05
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-05
  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-05
  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
Random Starts Specifications
  Number of initial stage random starts                         20
  Number of final stage optimizations                            4
  Number of initial stage iterations                            10
  Initial stage convergence criterion                    0.100D+01
  Random starts scale                                    0.500D+01
  Random seed for generating random starts                       0
Link                                                         LOGIT
Base Hazard                                   EQUAL ACROSS CLASSES

Input data file(s)
  ex7.30.dat
Input data format  FREE


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    U
      Category 1    0.460      230.000
      Category 2    0.540      270.000


RANDOM STARTS RESULTS RANKED FROM THE BEST TO THE WORST LOGLIKELIHOOD VALUES

Final stage loglikelihood values at local maxima, seeds, and initial stage start numbers:

             -98.989  851945           18
             -98.989  939021           8
             -98.989  608496           4
             -98.989  unperturbed      0



THE BEST LOGLIKELIHOOD VALUE HAS BEEN REPLICATED.  RERUN WITH AT LEAST TWICE THE
RANDOM STARTS TO CHECK THAT THE BEST LOGLIKELIHOOD IS STILL OBTAINED AND REPLICATED.


THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                        3

Loglikelihood

          H0 Value                         -98.989
          H0 Scaling Correction Factor      1.0162
            for MLR

Information Criteria

          Akaike (AIC)                     203.978
          Bayesian (BIC)                   216.621
          Sample-Size Adjusted BIC         207.099
            (n* = (n + 2) / 24)

Chi-Square Test of Model Fit for the Binary and Ordered Categorical
(Ordinal) Outcomes

          Pearson Chi-Square

          Value                              0.000
          Degrees of Freedom                     0
          P-Value                           1.0000

          Likelihood Ratio Chi-Square

          Value                              0.000
          Degrees of Freedom                     0
          P-Value                           1.0000



FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THE ESTIMATED MODEL

    Latent
   Classes

       1        229.99999          0.46000
       2        270.00001          0.54000


FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS
BASED ON ESTIMATED POSTERIOR PROBABILITIES

    Latent
   Classes

       1        229.99999          0.46000
       2        270.00001          0.54000


CLASSIFICATION QUALITY

     Entropy                         1.000


CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP

Class Counts and Proportions

    Latent
   Classes

       1              230          0.46000
       2              270          0.54000


Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)

           1        2

    1   1.000    0.000
    2   0.000    1.000


Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)

           1        2

    1   1.000    0.000
    2   0.000    1.000


Logits for the Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)

              1        2

    1     13.816    0.000
    2    -13.816    0.000


MODEL RESULTS

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

Latent Class 1

 T        ON
    X                  0.541      0.057      9.479      0.000

 Intercepts
    T                  0.000      0.000    999.000    999.000

 Thresholds
    U$1               15.000      0.000    999.000    999.000

Latent Class 2

 T        ON
    X                  0.541      0.057      9.479      0.000

 Intercepts
    T                  0.974      0.117      8.325      0.000

 Thresholds
    U$1              -15.000      0.000    999.000    999.000

Categorical Latent Variables

 Means
    C#1               -0.160      0.090     -1.787      0.074


RESULTS IN PROBABILITY SCALE

Latent Class 1

 U
    Category 1         1.000      0.000      0.000      1.000
    Category 2         0.000      0.000      0.000      1.000

Latent Class 2

 U
    Category 1         0.000      0.000      0.000      1.000
    Category 2         1.000      0.000      0.000      1.000


LATENT CLASS ODDS RATIO RESULTS

Latent Class 1 Compared to Latent Class 2

 U
    Category > 1       0.000      0.000    999.000    999.000


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.222E+00
       (ratio of smallest to largest eigenvalue)


LOGRANK OUTPUT

     LOGRANK TEST FOR SURVIVAL VARIABLE T COMPARING CLASS 2 AGAINST CLASS 1


          Chi-Square Value                             64.136
          Degrees of Freedom                                1
          P-value                                       0.000



TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION FOR LATENT CLASS 1


           NU
              X
              ________
 1                  0


           LAMBDA
              X
              ________
 X                  0


           THETA
              X
              ________
 X                  0


           ALPHA
              X
              ________
 1                  0


           BETA
              X
              ________
 X                  0


           PSI
              X
              ________
 X                  0


     PARAMETER SPECIFICATION FOR LATENT CLASS 2


           NU
              X
              ________
 1                  0


           LAMBDA
              X
              ________
 X                  0


           THETA
              X
              ________
 X                  0


           ALPHA
              X
              ________
 1                  0


           BETA
              X
              ________
 X                  0


           PSI
              X
              ________
 X                  0


     PARAMETER SPECIFICATION FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS 1
              U$1
              ________
 1                  0


           TAU(U) FOR LATENT CLASS 2
              U$1
              ________
 1                  0


     PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2
              ________      ________
 1                  1             0


           GAMMA(C)
              X
              ________
 C#1                0
 C#2                0


     PARAMETER SPECIFICATION FOR THE CENSORED/NOMINAL/COUNT MODEL PART


           NU(P) FOR LATENT CLASS 1
              T#1           T
              ________      ________
 1                  0             0


           KAPPA(P) FOR LATENT CLASS 1
              X
              ________
 T#1                0
 T                  2


           NU(P) FOR LATENT CLASS 2
              T#1           T
              ________      ________
 1                  0             3


           KAPPA(P) FOR LATENT CLASS 2
              X
              ________
 T#1                0
 T                  2


     STARTING VALUES FOR LATENT CLASS 1


           NU
              X
              ________
 1              0.000


           LAMBDA
              X
              ________
 X              1.000


           THETA
              X
              ________
 X              0.000


           ALPHA
              X
              ________
 1              0.000


           BETA
              X
              ________
 X              0.000


           PSI
              X
              ________
 X              0.560


     STARTING VALUES FOR LATENT CLASS 2


           NU
              X
              ________
 1              0.000


           LAMBDA
              X
              ________
 X              1.000


           THETA
              X
              ________
 X              0.000


           ALPHA
              X
              ________
 1              0.000


           BETA
              X
              ________
 X              0.000


           PSI
              X
              ________
 X              0.560


     STARTING VALUES FOR LATENT CLASS INDICATOR MODEL PART


           TAU(U) FOR LATENT CLASS 1
              U$1
              ________
 1             15.000


           TAU(U) FOR LATENT CLASS 2
              U$1
              ________
 1            -15.000


     STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART


           ALPHA(C)
              C#1           C#2
              ________      ________
 1              0.000         0.000


           GAMMA(C)
              X
              ________
 C#1            0.000
 C#2            0.000


     STARTING VALUES FOR THE CENSORED/NOMINAL/COUNT MODEL PART


           NU(P) FOR LATENT CLASS 1
              T#1           T
              ________      ________
 1            -20.000         0.000


           KAPPA(P) FOR LATENT CLASS 1
              X
              ________
 T#1            0.000
 T              0.000


           NU(P) FOR LATENT CLASS 2
              T#1           T
              ________      ________
 1            -20.000         0.000


           KAPPA(P) FOR LATENT CLASS 2
              X
              ________
 T#1            0.000
 T              0.000


PLOT INFORMATION

The following plots are available:

  Survival curves
  Sample proportions and estimated probabilities

     Beginning Time:  14:42:20
        Ending Time:  14:42:20
       Elapsed Time:  00:00:00



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