Mplus VERSION 6
MUTHEN & MUTHEN
04/25/2010 11:01 PM
INPUT INSTRUCTIONS
TITLE: cfa1.inp normal, no missing
MONTECARLO: NAMES ARE y1-y10;
NOBSERVATIONS = 150;
NREPS = 10000;
SEED = 53487;
CLASSES = C(1);
GENCLASSES = C(1);
SAVE = cfa1.sav;
ANALYSIS: TYPE = MIXTURE;
ESTIMATOR = ML;
MODEL MONTECARLO:
%OVERALL%
f1 BY y1-y5*.8;
f2 BY y6-y10*.8;
f1@1 f2@1;
y1-y10*.36;
f1 WITH f2*.25;
MODEL:
%OVERALL%
f1 BY y1-y5*.8;
f2 BY y6-y10*.8;
f1@1 f2@1;
y1-y10*.36;
f1 WITH f2*.25;
OUTPUT: TECH9;
INPUT READING TERMINATED NORMALLY
cfa1.inp normal, no missing
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 150
Number of replications
Requested 10000
Completed 10000
Value of seed 53487
Number of dependent variables 10
Number of independent variables 0
Number of continuous latent variables 2
Number of categorical latent variables 1
Observed dependent variables
Continuous
Y1 Y2 Y3 Y4 Y5 Y6
Y7 Y8 Y9 Y10
Continuous latent variables
F1 F2
Categorical latent variables
C
Estimator ML
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
SAMPLE STATISTICS FOR THE FIRST REPLICATION
SAMPLE STATISTICS
Means
Y1 Y2 Y3 Y4 Y5
________ ________ ________ ________ ________
1 0.108 0.040 0.069 0.007 -0.048
Means
Y6 Y7 Y8 Y9 Y10
________ ________ ________ ________ ________
1 -0.084 0.036 -0.005 -0.026 -0.015
Covariances
Y1 Y2 Y3 Y4 Y5
________ ________ ________ ________ ________
Y1 0.905
Y2 0.611 0.944
Y3 0.570 0.538 0.966
Y4 0.579 0.596 0.600 0.943
Y5 0.520 0.542 0.514 0.596 0.934
Y6 0.068 0.147 0.093 0.079 0.119
Y7 0.084 0.125 0.063 0.150 0.094
Y8 0.123 0.173 0.159 0.197 0.155
Y9 0.073 0.083 0.147 0.138 0.108
Y10 0.233 0.169 0.142 0.222 0.141
Covariances
Y6 Y7 Y8 Y9 Y10
________ ________ ________ ________ ________
Y6 0.875
Y7 0.632 1.106
Y8 0.578 0.722 1.048
Y9 0.529 0.647 0.691 0.955
Y10 0.612 0.765 0.773 0.734 1.144
Correlations
Y1 Y2 Y3 Y4 Y5
________ ________ ________ ________ ________
Y1 1.000
Y2 0.661 1.000
Y3 0.610 0.563 1.000
Y4 0.627 0.632 0.629 1.000
Y5 0.565 0.578 0.541 0.635 1.000
Y6 0.076 0.162 0.101 0.087 0.132
Y7 0.084 0.122 0.061 0.146 0.093
Y8 0.126 0.174 0.158 0.199 0.157
Y9 0.079 0.087 0.153 0.146 0.114
Y10 0.229 0.162 0.135 0.214 0.136
Correlations
Y6 Y7 Y8 Y9 Y10
________ ________ ________ ________ ________
Y6 1.000
Y7 0.643 1.000
Y8 0.604 0.671 1.000
Y9 0.578 0.630 0.691 1.000
Y10 0.612 0.680 0.706 0.702 1.000
TESTS OF MODEL FIT
Number of Free Parameters 31
Loglikelihood
H0 Value
Mean -1686.727
Std Dev 27.609
Number of successful computations 10000
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.990 -1750.955 -1751.125
0.980 0.980 -1743.429 -1743.685
0.950 0.951 -1732.142 -1731.630
0.900 0.902 -1722.112 -1721.814
0.800 0.801 -1709.964 -1709.861
0.700 0.698 -1701.206 -1701.340
0.500 0.501 -1686.727 -1686.679
0.300 0.296 -1672.249 -1672.616
0.200 0.200 -1663.491 -1663.520
0.100 0.103 -1651.343 -1650.843
0.050 0.049 -1641.313 -1641.642
0.020 0.020 -1630.026 -1630.360
0.010 0.009 -1622.500 -1623.637
Information Criteria
Akaike (AIC)
Mean 3435.455
Std Dev 55.219
Number of successful computations 10000
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.991 3306.999 3309.161
0.980 0.980 3322.052 3322.665
0.950 0.951 3344.625 3345.274
0.900 0.897 3364.686 3363.640
0.800 0.800 3388.983 3389.014
0.700 0.704 3406.498 3407.200
0.500 0.499 3435.455 3435.348
0.300 0.302 3464.412 3464.679
0.200 0.199 3481.927 3481.685
0.100 0.098 3506.223 3505.339
0.050 0.049 3526.284 3525.242
0.020 0.020 3548.858 3549.350
0.010 0.010 3563.911 3564.177
Bayesian (BIC)
Mean 3528.785
Std Dev 55.219
Number of successful computations 10000
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.991 3400.329 3402.491
0.980 0.980 3415.381 3415.995
0.950 0.951 3437.955 3438.604
0.900 0.897 3458.016 3456.970
0.800 0.800 3482.312 3482.343
0.700 0.704 3499.828 3500.529
0.500 0.499 3528.785 3528.678
0.300 0.302 3557.741 3558.009
0.200 0.199 3575.257 3575.015
0.100 0.098 3599.553 3598.669
0.050 0.049 3619.614 3618.572
0.020 0.020 3642.188 3642.680
0.010 0.010 3657.240 3657.507
Sample-Size Adjusted BIC (n* = (n + 2) / 24)
Mean 3430.675
Std Dev 55.219
Number of successful computations 10000
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.991 3302.220 3304.381
0.980 0.980 3317.272 3317.885
0.950 0.951 3339.846 3340.495
0.900 0.897 3359.907 3358.861
0.800 0.800 3384.203 3384.234
0.700 0.704 3401.719 3402.420
0.500 0.499 3430.675 3430.569
0.300 0.302 3459.632 3459.900
0.200 0.199 3477.148 3476.906
0.100 0.098 3501.444 3500.560
0.050 0.049 3521.505 3520.463
0.020 0.020 3544.078 3544.571
0.010 0.010 3559.131 3559.398
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THE ESTIMATED MODEL
Latent
Classes
1 150.00000 1.00000
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS
BASED ON ESTIMATED POSTERIOR PROBABILITIES
Latent
Classes
1 150.00000 1.00000
CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP
Class Counts and Proportions
Latent
Classes
1 150 1.00000
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1
1 1.000
MODEL RESULTS
ESTIMATES S. E. M. S. E. 95% % Sig
Population Average Std. Dev. Average Cover Coeff
Latent Class 1
F1 BY
Y1 0.800 0.7979 0.0706 0.0699 0.0050 0.947 1.000
Y2 0.800 0.7977 0.0710 0.0699 0.0050 0.942 1.000
Y3 0.800 0.7964 0.0713 0.0698 0.0051 0.945 1.000
Y4 0.800 0.7971 0.0707 0.0699 0.0050 0.945 1.000
Y5 0.800 0.7973 0.0702 0.0698 0.0049 0.949 1.000
F2 BY
Y6 0.800 0.7966 0.0696 0.0698 0.0049 0.951 1.000
Y7 0.800 0.7970 0.0700 0.0698 0.0049 0.947 1.000
Y8 0.800 0.7958 0.0704 0.0698 0.0050 0.947 1.000
Y9 0.800 0.7971 0.0702 0.0698 0.0049 0.947 1.000
Y10 0.800 0.7968 0.0695 0.0698 0.0048 0.948 1.000
F1 WITH
F2 0.250 0.2507 0.0873 0.0852 0.0076 0.942 0.809
Means
F1 0.000 0.0000 0.0000 0.0000 0.0000 1.000 0.000
F2 0.000 0.0000 0.0000 0.0000 0.0000 1.000 0.000
Intercepts
Y1 0.000 0.0001 0.0814 0.0814 0.0066 0.948 0.052
Y2 0.000 -0.0003 0.0828 0.0814 0.0069 0.943 0.057
Y3 0.000 0.0012 0.0822 0.0813 0.0068 0.945 0.055
Y4 0.000 -0.0004 0.0822 0.0813 0.0068 0.949 0.051
Y5 0.000 0.0007 0.0813 0.0813 0.0066 0.949 0.051
Y6 0.000 0.0005 0.0823 0.0813 0.0068 0.943 0.057
Y7 0.000 -0.0003 0.0822 0.0813 0.0068 0.944 0.056
Y8 0.000 -0.0003 0.0818 0.0813 0.0067 0.950 0.050
Y9 0.000 0.0006 0.0811 0.0813 0.0066 0.952 0.048
Y10 0.000 -0.0003 0.0818 0.0813 0.0067 0.947 0.053
Variances
F1 1.000 1.0000 0.0000 0.0000 0.0000 1.000 0.000
F2 1.000 1.0000 0.0000 0.0000 0.0000 1.000 0.000
Residual Variances
Y1 0.360 0.3549 0.0521 0.0516 0.0027 0.932 1.000
Y2 0.360 0.3551 0.0523 0.0516 0.0028 0.935 1.000
Y3 0.360 0.3547 0.0521 0.0515 0.0027 0.935 1.000
Y4 0.360 0.3553 0.0522 0.0516 0.0028 0.937 1.000
Y5 0.360 0.3544 0.0526 0.0515 0.0028 0.931 1.000
Y6 0.360 0.3544 0.0522 0.0515 0.0028 0.934 1.000
Y7 0.360 0.3547 0.0526 0.0516 0.0028 0.930 1.000
Y8 0.360 0.3554 0.0521 0.0516 0.0027 0.938 1.000
Y9 0.360 0.3546 0.0526 0.0516 0.0028 0.935 1.000
Y10 0.360 0.3552 0.0519 0.0516 0.0027 0.936 1.000
QUALITY OF NUMERICAL RESULTS
Average Condition Number for the Information Matrix 0.105E-01
(ratio of smallest to largest eigenvalue)
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION FOR LATENT CLASS 1
NU
Y1 Y2 Y3 Y4 Y5
________ ________ ________ ________ ________
1 1 2 3 4 5
NU
Y6 Y7 Y8 Y9 Y10
________ ________ ________ ________ ________
1 6 7 8 9 10
LAMBDA
F1 F2
________ ________
Y1 11 0
Y2 12 0
Y3 13 0
Y4 14 0
Y5 15 0
Y6 0 16
Y7 0 17
Y8 0 18
Y9 0 19
Y10 0 20
THETA
Y1 Y2 Y3 Y4 Y5
________ ________ ________ ________ ________
Y1 21
Y2 0 22
Y3 0 0 23
Y4 0 0 0 24
Y5 0 0 0 0 25
Y6 0 0 0 0 0
Y7 0 0 0 0 0
Y8 0 0 0 0 0
Y9 0 0 0 0 0
Y10 0 0 0 0 0
THETA
Y6 Y7 Y8 Y9 Y10
________ ________ ________ ________ ________
Y6 26
Y7 0 27
Y8 0 0 28
Y9 0 0 0 29
Y10 0 0 0 0 30
ALPHA
F1 F2
________ ________
1 0 0
BETA
F1 F2
________ ________
F1 0 0
F2 0 0
PSI
F1 F2
________ ________
F1 0
F2 31 0
PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C#1
________
1 0
STARTING VALUES FOR LATENT CLASS 1
NU
Y1 Y2 Y3 Y4 Y5
________ ________ ________ ________ ________
1 0.000 0.000 0.000 0.000 0.000
NU
Y6 Y7 Y8 Y9 Y10
________ ________ ________ ________ ________
1 0.000 0.000 0.000 0.000 0.000
LAMBDA
F1 F2
________ ________
Y1 0.800 0.000
Y2 0.800 0.000
Y3 0.800 0.000
Y4 0.800 0.000
Y5 0.800 0.000
Y6 0.000 0.800
Y7 0.000 0.800
Y8 0.000 0.800
Y9 0.000 0.800
Y10 0.000 0.800
THETA
Y1 Y2 Y3 Y4 Y5
________ ________ ________ ________ ________
Y1 0.360
Y2 0.000 0.360
Y3 0.000 0.000 0.360
Y4 0.000 0.000 0.000 0.360
Y5 0.000 0.000 0.000 0.000 0.360
Y6 0.000 0.000 0.000 0.000 0.000
Y7 0.000 0.000 0.000 0.000 0.000
Y8 0.000 0.000 0.000 0.000 0.000
Y9 0.000 0.000 0.000 0.000 0.000
Y10 0.000 0.000 0.000 0.000 0.000
THETA
Y6 Y7 Y8 Y9 Y10
________ ________ ________ ________ ________
Y6 0.360
Y7 0.000 0.360
Y8 0.000 0.000 0.360
Y9 0.000 0.000 0.000 0.360
Y10 0.000 0.000 0.000 0.000 0.360
ALPHA
F1 F2
________ ________
1 0.000 0.000
BETA
F1 F2
________ ________
F1 0.000 0.000
F2 0.000 0.000
PSI
F1 F2
________ ________
F1 1.000
F2 0.250 1.000
STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C#1
________
1 0.000
POPULATION VALUES FOR LATENT CLASS 1
NU
Y1 Y2 Y3 Y4 Y5
________ ________ ________ ________ ________
1 0.000 0.000 0.000 0.000 0.000
NU
Y6 Y7 Y8 Y9 Y10
________ ________ ________ ________ ________
1 0.000 0.000 0.000 0.000 0.000
LAMBDA
F1 F2
________ ________
Y1 0.800 0.000
Y2 0.800 0.000
Y3 0.800 0.000
Y4 0.800 0.000
Y5 0.800 0.000
Y6 0.000 0.800
Y7 0.000 0.800
Y8 0.000 0.800
Y9 0.000 0.800
Y10 0.000 0.800
THETA
Y1 Y2 Y3 Y4 Y5
________ ________ ________ ________ ________
Y1 0.360
Y2 0.000 0.360
Y3 0.000 0.000 0.360
Y4 0.000 0.000 0.000 0.360
Y5 0.000 0.000 0.000 0.000 0.360
Y6 0.000 0.000 0.000 0.000 0.000
Y7 0.000 0.000 0.000 0.000 0.000
Y8 0.000 0.000 0.000 0.000 0.000
Y9 0.000 0.000 0.000 0.000 0.000
Y10 0.000 0.000 0.000 0.000 0.000
THETA
Y6 Y7 Y8 Y9 Y10
________ ________ ________ ________ ________
Y6 0.360
Y7 0.000 0.360
Y8 0.000 0.000 0.360
Y9 0.000 0.000 0.000 0.360
Y10 0.000 0.000 0.000 0.000 0.360
ALPHA
F1 F2
________ ________
1 0.000 0.000
BETA
F1 F2
________ ________
F1 0.000 0.000
F2 0.000 0.000
PSI
F1 F2
________ ________
F1 1.000
F2 0.250 1.000
POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C#1
________
1 0.000
TECHNICAL 9 OUTPUT
Error messages for each replication (if any)
SAVEDATA INFORMATION
Order of variables
Y1
Y2
Y3
Y4
Y5
Y6
Y7
Y8
Y9
Y10
C
Save file
cfa1.sav
Save file format Free
Save file record length 5000
Beginning Time: 23:01:26
Ending Time: 23:03:08
Elapsed Time: 00:01:42
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