Mplus VERSION 7.4
MUTHEN & MUTHEN
06/01/2016 7:05 PM
INPUT INSTRUCTIONS
TITLE: Example: MAR simulation
DATA:
FILE = n500mix00xreplist.dat;
TYPE = MONTECARLO;
VARIABLE:
NAMES = y m tx x;
USEVARIABLES = y-x ymiss;
CATEGORICAL = ymiss;
MISSING = ALL(999);
DEFINE:
IF(y EQ _missing)THEN ymiss=1 ELSE ymiss=0;
ANALYSIS:
ESTIMATOR = MLR;
MODEL:
y on m*1 tx*0 x*0;
y*.75;
m on tx*-.5 x*.5;
m*.5;
[y-m*0];
ymiss ON m*2;
[ymiss$1*0.5];
INPUT READING TERMINATED NORMALLY
Example: MAR simulation
SUMMARY OF ANALYSIS
Number of groups 1
Average number of observations 500
Number of replications
Requested 500
Completed 500
Number of dependent variables 3
Number of independent variables 2
Number of continuous latent variables 0
Observed dependent variables
Continuous
Y M
Binary and ordered categorical (ordinal)
YMISS
Observed independent variables
TX X
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
Maximum number of iterations for H1 2000
Convergence criterion for H1 0.100D-03
Optimization algorithm EMA
Integration Specifications
Type STANDARD
Number of integration points 15
Dimensions of numerical integration 0
Adaptive quadrature ON
Link LOGIT
Cholesky OFF
Input data file(s)
Multiple data files from
n500mix00xreplist.dat
Input data format FREE
SUMMARY OF DATA FOR THE FIRST REPLICATION
Number of missing data patterns 2
Number of y missing data patterns 2
Number of u missing data patterns 1
SUMMARY OF MISSING DATA PATTERNS FOR THE FIRST REPLICATION
MISSING DATA PATTERNS FOR Y (x = not missing)
1 2
Y x
M x x
TX x x
X x x
MISSING DATA PATTERN FREQUENCIES FOR Y
Pattern Frequency Pattern Frequency
1 319 2 181
COVARIANCE COVERAGE OF DATA FOR THE FIRST REPLICATION
Minimum covariance coverage value 0.100
PROPORTION OF DATA PRESENT FOR Y
Covariance Coverage
Y M TX X
________ ________ ________ ________
Y 0.638
M 0.638 1.000
TX 0.638 1.000 1.000
X 0.638 1.000 1.000 1.000
UNIVARIATE PROPORTIONS FOR CATEGORICAL VARIABLES FOR THE FIRST REPLICATION
YMISS
Category 1 0.638
Category 2 0.362
SAMPLE STATISTICS
NOTE: These are average results over 500 data sets.
SAMPLE STATISTICS
Means
Y M TX X
________ ________ ________ ________
1 -0.249 -0.249 0.500 0.002
Covariances
Y M TX X
________ ________ ________ ________
Y 1.563
M 0.812 0.812
TX -0.126 -0.124 0.249
X 0.500 0.501 0.001 1.001
Correlations
Y M TX X
________ ________ ________ ________
Y 1.000
M 0.721 1.000
TX -0.202 -0.277 1.000
X 0.399 0.556 0.001 1.000
MODEL FIT INFORMATION
Number of Free Parameters 11
Loglikelihood
H0 Value
Mean -1174.523
Std Dev 23.441
Number of successful computations 500
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.994 -1229.055 -1226.349
0.980 0.978 -1222.664 -1224.358
0.950 0.952 -1213.082 -1212.521
0.900 0.896 -1204.565 -1204.971
0.800 0.782 -1194.251 -1195.689
0.700 0.698 -1186.816 -1187.081
0.500 0.498 -1174.523 -1174.561
0.300 0.312 -1162.231 -1161.563
0.200 0.216 -1154.795 -1153.910
0.100 0.118 -1144.481 -1142.670
0.050 0.052 -1135.965 -1135.948
0.020 0.014 -1126.382 -1128.460
0.010 0.006 -1119.992 -1125.664
Information Criteria
Akaike (AIC)
Mean 2371.046
Std Dev 46.883
Number of successful computations 500
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.994 2261.983 2266.532
0.980 0.986 2274.764 2277.710
0.950 0.948 2293.929 2293.404
0.900 0.882 2310.962 2305.950
0.800 0.784 2331.590 2328.267
0.700 0.688 2346.461 2344.985
0.500 0.502 2371.046 2371.103
0.300 0.302 2395.631 2396.160
0.200 0.218 2410.503 2413.041
0.100 0.104 2431.131 2431.164
0.050 0.048 2448.163 2446.174
0.020 0.022 2467.329 2469.451
0.010 0.006 2480.109 2473.701
Bayesian (BIC)
Mean 2417.407
Std Dev 46.883
Number of successful computations 500
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.994 2308.344 2312.893
0.980 0.986 2321.124 2324.070
0.950 0.948 2340.290 2339.765
0.900 0.882 2357.322 2352.311
0.800 0.784 2377.951 2374.628
0.700 0.688 2392.822 2391.345
0.500 0.502 2417.407 2417.464
0.300 0.302 2441.992 2442.520
0.200 0.218 2456.863 2459.401
0.100 0.104 2477.492 2477.525
0.050 0.048 2494.524 2492.535
0.020 0.022 2513.690 2515.812
0.010 0.006 2526.470 2520.061
Sample-Size Adjusted BIC (n* = (n + 2) / 24)
Mean 2382.492
Std Dev 46.883
Number of successful computations 500
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.994 2273.429 2277.978
0.980 0.986 2286.210 2289.156
0.950 0.948 2305.375 2304.850
0.900 0.882 2322.408 2317.396
0.800 0.784 2343.036 2339.713
0.700 0.688 2357.907 2356.431
0.500 0.502 2382.492 2382.549
0.300 0.302 2407.077 2407.606
0.200 0.218 2421.949 2424.487
0.100 0.104 2442.577 2442.610
0.050 0.048 2459.609 2457.620
0.020 0.022 2478.775 2480.897
0.010 0.006 2491.555 2485.147
MODEL RESULTS
ESTIMATES S. E. M. S. E. 95% % Sig
Population Average Std. Dev. Average Cover Coeff
Y ON
M 1.000 0.9995 0.0760 0.0756 0.0058 0.946 1.000
TX 0.000 -0.0082 0.0979 0.1009 0.0096 0.966 0.034
X 0.000 -0.0009 0.0606 0.0586 0.0037 0.936 0.064
M ON
TX -0.500 -0.5000 0.0653 0.0631 0.0043 0.936 1.000
X 0.500 0.5008 0.0315 0.0315 0.0010 0.952 1.000
YMISS ON
M 2.000 2.0363 0.2004 0.1944 0.0414 0.942 1.000
Intercepts
Y 0.000 0.0036 0.0754 0.0769 0.0057 0.958 0.042
M 0.000 0.0010 0.0462 0.0447 0.0021 0.944 0.056
Thresholds
YMISS$1 0.500 0.5034 0.1145 0.1175 0.0131 0.958 0.994
Residual Variances
Y 0.750 0.7437 0.0556 0.0579 0.0031 0.952 1.000
M 0.500 0.4966 0.0316 0.0311 0.0010 0.946 1.000
QUALITY OF NUMERICAL RESULTS
Average Condition Number for the Information Matrix 0.118E-01
(ratio of smallest to largest eigenvalue)
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION
TAU
YMISS$1
________
1 11
NU
YMISS Y M TX X
________ ________ ________ ________ ________
1 0 0 0 0 0
LAMBDA
YMISS Y M TX X
________ ________ ________ ________ ________
YMISS 0 0 0 0 0
Y 0 0 0 0 0
M 0 0 0 0 0
TX 0 0 0 0 0
X 0 0 0 0 0
THETA
YMISS Y M TX X
________ ________ ________ ________ ________
YMISS 0
Y 0 0
M 0 0 0
TX 0 0 0 0
X 0 0 0 0 0
ALPHA
YMISS Y M TX X
________ ________ ________ ________ ________
1 0 1 2 0 0
BETA
YMISS Y M TX X
________ ________ ________ ________ ________
YMISS 0 0 3 0 0
Y 0 0 4 5 6
M 0 0 0 7 8
TX 0 0 0 0 0
X 0 0 0 0 0
PSI
YMISS Y M TX X
________ ________ ________ ________ ________
YMISS 0
Y 0 9
M 0 0 10
TX 0 0 0 0
X 0 0 0 0 0
STARTING VALUES
TAU
YMISS$1
________
1 0.500
NU
YMISS Y M TX X
________ ________ ________ ________ ________
1 0.000 0.000 0.000 0.000 0.000
LAMBDA
YMISS Y M TX X
________ ________ ________ ________ ________
YMISS 1.000 0.000 0.000 0.000 0.000
Y 0.000 1.000 0.000 0.000 0.000
M 0.000 0.000 1.000 0.000 0.000
TX 0.000 0.000 0.000 1.000 0.000
X 0.000 0.000 0.000 0.000 1.000
THETA
YMISS Y M TX X
________ ________ ________ ________ ________
YMISS 0.000
Y 0.000 0.000
M 0.000 0.000 0.000
TX 0.000 0.000 0.000 0.000
X 0.000 0.000 0.000 0.000 0.000
ALPHA
YMISS Y M TX X
________ ________ ________ ________ ________
1 0.000 0.000 0.000 0.000 0.000
BETA
YMISS Y M TX X
________ ________ ________ ________ ________
YMISS 0.000 0.000 2.000 0.000 0.000
Y 0.000 0.000 1.000 0.000 0.000
M 0.000 0.000 0.000 -0.500 0.500
TX 0.000 0.000 0.000 0.000 0.000
X 0.000 0.000 0.000 0.000 0.000
PSI
YMISS Y M TX X
________ ________ ________ ________ ________
YMISS 1.000
Y 0.000 0.750
M 0.000 0.000 0.500
TX 0.000 0.000 0.000 0.500
X 0.000 0.000 0.000 0.000 0.500
DIAGRAM INFORMATION
Mplus diagrams are currently not available for Monte Carlo analysis.
No diagram output was produced.
Beginning Time: 19:05:45
Ending Time: 19:05:51
Elapsed Time: 00:00:06
MUTHEN & MUTHEN
3463 Stoner Ave.
Los Angeles, CA 90066
Tel: (310) 391-9971
Fax: (310) 391-8971
Web: www.StatModel.com
Support: Support@StatModel.com
Copyright (c) 1998-2015 Muthen & Muthen
Back to examples