Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 11:20 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
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 0.008 -0.111 -3.990 0.10% -0.832 -0.259 0.005
1000.000 1.022 -0.042 2.840 0.10% 0.272 0.881
W -0.101 0.106 -2.354 0.91% -1.109 -0.363 -0.136
110.000 1.088 -0.309 2.752 0.91% 0.192 0.742
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: 23:20:36
Ending Time: 23:20:37
Elapsed Time: 00:00:01
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