Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 10:24 PM
INPUT INSTRUCTIONS
title:
this is an example of a mixture model with
different means for continuous outcomes
montecarlo:
names are y1-y4;
genclasses = c(3);
classes = c(3);
nobs = 500;
seed = 3454367;
nrep = 1;
save = ex7.22.dat;
analysis:
type = mixture;
model population:
%overall%
[c#1*0 c#2*0];
y1 with y2-y4*.5;
y2 with y3-y4*.25;
y3 with y4*.10;
[y1-y4*0];
y1-y4*1;
%c#2%
[y1-y4*-2];
%c#3%
[y1-y4*2];
model:
%overall%
[c#1*0 c#2*0];
y1 with y2-y4*.5;
y2 with y3-y4*.25;
y3 with y4*.10;
[y1-y4*0];
y1-y4*1;
%c#2%
[y1-y4*-2];
%c#3%
[y1-y4*2];
output:
tech8 tech9;
INPUT READING TERMINATED NORMALLY
this is an example of a mixture model with
different means for continuous outcomes
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 500
Number of replications
Requested 1
Completed 1
Value of seed 3454367
Number of dependent variables 4
Number of independent variables 0
Number of continuous latent variables 0
Number of categorical latent variables 1
Observed dependent variables
Continuous
Y1 Y2 Y3 Y4
Categorical latent variables
C
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
SAMPLE STATISTICS FOR THE FIRST REPLICATION
SAMPLE STATISTICS
Means
Y1 Y2 Y3 Y4
________ ________ ________ ________
-0.089 -0.118 -0.120 -0.123
Covariances
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 3.643
Y2 3.157 3.691
Y3 3.142 2.926 3.660
Y4 3.022 2.833 2.663 3.504
Correlations
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.000
Y2 0.861 1.000
Y3 0.861 0.796 1.000
Y4 0.846 0.788 0.744 1.000
MODEL FIT INFORMATION
Number of Free Parameters 24
Loglikelihood
H0 Value
Mean -3054.963
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 -3054.963 -3054.963
0.980 0.000 -3054.963 -3054.963
0.950 0.000 -3054.963 -3054.963
0.900 0.000 -3054.963 -3054.963
0.800 0.000 -3054.963 -3054.963
0.700 0.000 -3054.963 -3054.963
0.500 0.000 -3054.963 -3054.963
0.300 0.000 -3054.963 -3054.963
0.200 0.000 -3054.963 -3054.963
0.100 0.000 -3054.963 -3054.963
0.050 0.000 -3054.963 -3054.963
0.020 0.000 -3054.963 -3054.963
0.010 0.000 -3054.963 -3054.963
Information Criteria
Akaike (AIC)
Mean 6157.926
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 6157.926 6157.926
0.980 0.000 6157.926 6157.926
0.950 0.000 6157.926 6157.926
0.900 0.000 6157.926 6157.926
0.800 0.000 6157.926 6157.926
0.700 0.000 6157.926 6157.926
0.500 0.000 6157.926 6157.926
0.300 0.000 6157.926 6157.926
0.200 0.000 6157.926 6157.926
0.100 0.000 6157.926 6157.926
0.050 0.000 6157.926 6157.926
0.020 0.000 6157.926 6157.926
0.010 0.000 6157.926 6157.926
Bayesian (BIC)
Mean 6259.077
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 6259.077 6259.077
0.980 0.000 6259.077 6259.077
0.950 0.000 6259.077 6259.077
0.900 0.000 6259.077 6259.077
0.800 0.000 6259.077 6259.077
0.700 0.000 6259.077 6259.077
0.500 0.000 6259.077 6259.077
0.300 0.000 6259.077 6259.077
0.200 0.000 6259.077 6259.077
0.100 0.000 6259.077 6259.077
0.050 0.000 6259.077 6259.077
0.020 0.000 6259.077 6259.077
0.010 0.000 6259.077 6259.077
Sample-Size Adjusted BIC (n* = (n + 2) / 24)
Mean 6182.899
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 6182.899 6182.899
0.980 0.000 6182.899 6182.899
0.950 0.000 6182.899 6182.899
0.900 0.000 6182.899 6182.899
0.800 0.000 6182.899 6182.899
0.700 0.000 6182.899 6182.899
0.500 0.000 6182.899 6182.899
0.300 0.000 6182.899 6182.899
0.200 0.000 6182.899 6182.899
0.100 0.000 6182.899 6182.899
0.050 0.000 6182.899 6182.899
0.020 0.000 6182.899 6182.899
0.010 0.000 6182.899 6182.899
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THE ESTIMATED MODEL
Latent
Classes
1 162.30842 0.32462
2 171.08814 0.34218
3 166.60343 0.33321
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON ESTIMATED POSTERIOR PROBABILITIES
Latent
Classes
1 162.30842 0.32462
2 171.08814 0.34218
3 166.60343 0.33321
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP
Class Counts and Proportions
Latent
Classes
1 164 0.32800
2 169 0.33800
3 167 0.33400
CLASSIFICATION QUALITY
Entropy 0.812
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1 2 3
1 0.869 0.084 0.047
2 0.069 0.931 0.000
3 0.049 0.000 0.951
Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)
1 2 3
1 0.878 0.072 0.050
2 0.080 0.920 0.000
3 0.047 0.000 0.953
Logits for the Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)
1 2 3
1 2.858 0.356 0.000
2 10.165 12.602 0.000
3 -3.017 -13.339 0.000
MODEL RESULTS
ESTIMATES S. E. M. S. E. 95% % Sig
Population Average Std. Dev. Average Cover Coeff
Latent Class 1
Y1 WITH
Y2 0.500 0.4415 0.0000 0.0719 0.0034 1.000 1.000
Y3 0.500 0.3968 0.0000 0.0621 0.0106 1.000 1.000
Y4 0.500 0.4756 0.0000 0.0685 0.0006 1.000 1.000
Y2 WITH
Y3 0.250 0.1590 0.0000 0.0548 0.0083 1.000 1.000
Y4 0.250 0.2643 0.0000 0.0778 0.0002 1.000 1.000
Y3 WITH
Y4 0.100 0.0646 0.0000 0.0539 0.0013 1.000 0.000
Means
Y1 0.000 -0.0760 0.0000 0.1099 0.0058 1.000 0.000
Y2 0.000 -0.0736 0.0000 0.1113 0.0054 1.000 0.000
Y3 0.000 -0.2679 0.0000 0.1236 0.0718 0.000 1.000
Y4 0.000 -0.1241 0.0000 0.1334 0.0154 1.000 0.000
Variances
Y1 1.000 0.9514 0.0000 0.0869 0.0024 1.000 1.000
Y2 1.000 0.9514 0.0000 0.0891 0.0024 1.000 1.000
Y3 1.000 0.8474 0.0000 0.0698 0.0233 0.000 1.000
Y4 1.000 1.0947 0.0000 0.1015 0.0090 1.000 1.000
Latent Class 2
Y1 WITH
Y2 0.500 0.4415 0.0000 0.0719 0.0034 1.000 1.000
Y3 0.500 0.3968 0.0000 0.0621 0.0106 1.000 1.000
Y4 0.500 0.4756 0.0000 0.0685 0.0006 1.000 1.000
Y2 WITH
Y3 0.250 0.1590 0.0000 0.0548 0.0083 1.000 1.000
Y4 0.250 0.2643 0.0000 0.0778 0.0002 1.000 1.000
Y3 WITH
Y4 0.100 0.0646 0.0000 0.0539 0.0013 1.000 0.000
Means
Y1 -2.000 -2.0653 0.0000 0.1086 0.0043 1.000 1.000
Y2 -2.000 -2.1260 0.0000 0.1010 0.0159 1.000 1.000
Y3 -2.000 -2.0593 0.0000 0.0934 0.0035 1.000 1.000
Y4 -2.000 -1.9865 0.0000 0.0976 0.0002 1.000 1.000
Variances
Y1 1.000 0.9514 0.0000 0.0869 0.0024 1.000 1.000
Y2 1.000 0.9514 0.0000 0.0891 0.0024 1.000 1.000
Y3 1.000 0.8474 0.0000 0.0698 0.0233 0.000 1.000
Y4 1.000 1.0947 0.0000 0.1015 0.0090 1.000 1.000
Latent Class 3
Y1 WITH
Y2 0.500 0.4415 0.0000 0.0719 0.0034 1.000 1.000
Y3 0.500 0.3968 0.0000 0.0621 0.0106 1.000 1.000
Y4 0.500 0.4756 0.0000 0.0685 0.0006 1.000 1.000
Y2 WITH
Y3 0.250 0.1590 0.0000 0.0548 0.0083 1.000 1.000
Y4 0.250 0.2643 0.0000 0.0778 0.0002 1.000 1.000
Y3 WITH
Y4 0.100 0.0646 0.0000 0.0539 0.0013 1.000 0.000
Means
Y1 2.000 1.9279 0.0000 0.0903 0.0052 1.000 1.000
Y2 2.000 1.9018 0.0000 0.0984 0.0096 1.000 1.000
Y3 2.000 2.0147 0.0000 0.0766 0.0002 1.000 1.000
Y4 2.000 1.7915 0.0000 0.0955 0.0435 0.000 1.000
Variances
Y1 1.000 0.9514 0.0000 0.0869 0.0024 1.000 1.000
Y2 1.000 0.9514 0.0000 0.0891 0.0024 1.000 1.000
Y3 1.000 0.8474 0.0000 0.0698 0.0233 0.000 1.000
Y4 1.000 1.0947 0.0000 0.1015 0.0090 1.000 1.000
Categorical Latent Variables
Means
C#1 0.000 -0.0261 0.0000 0.1360 0.0007 1.000 0.000
C#2 0.000 0.0266 0.0000 0.1349 0.0007 1.000 0.000
QUALITY OF NUMERICAL RESULTS
Average Condition Number for the Information Matrix 0.687E-02
(ratio of smallest to largest eigenvalue)
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION FOR LATENT CLASS 1
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
1 2 3 4
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 5
Y2 6 7
Y3 8 9 10
Y4 11 12 13 14
PARAMETER SPECIFICATION FOR LATENT CLASS 2
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
15 16 17 18
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 5
Y2 6 7
Y3 8 9 10
Y4 11 12 13 14
PARAMETER SPECIFICATION FOR LATENT CLASS 3
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
19 20 21 22
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 5
Y2 6 7
Y3 8 9 10
Y4 11 12 13 14
PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C#1 C#2 C#3
________ ________ ________
23 24 0
STARTING VALUES FOR LATENT CLASS 1
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
0.000 0.000 0.000 0.000
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.000
Y2 0.500 1.000
Y3 0.500 0.250 1.000
Y4 0.500 0.250 0.100 1.000
STARTING VALUES FOR LATENT CLASS 2
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
-2.000 -2.000 -2.000 -2.000
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.000
Y2 0.500 1.000
Y3 0.500 0.250 1.000
Y4 0.500 0.250 0.100 1.000
STARTING VALUES FOR LATENT CLASS 3
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
2.000 2.000 2.000 2.000
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.000
Y2 0.500 1.000
Y3 0.500 0.250 1.000
Y4 0.500 0.250 0.100 1.000
STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C#1 C#2 C#3
________ ________ ________
0.000 0.000 0.000
POPULATION VALUES FOR LATENT CLASS 1
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
0.000 0.000 0.000 0.000
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.000
Y2 0.500 1.000
Y3 0.500 0.250 1.000
Y4 0.500 0.250 0.100 1.000
POPULATION VALUES FOR LATENT CLASS 2
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
-2.000 -2.000 -2.000 -2.000
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.000
Y2 0.500 1.000
Y3 0.500 0.250 1.000
Y4 0.500 0.250 0.100 1.000
POPULATION VALUES FOR LATENT CLASS 3
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
2.000 2.000 2.000 2.000
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.000
Y2 0.500 1.000
Y3 0.500 0.250 1.000
Y4 0.500 0.250 0.100 1.000
POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C#1 C#2 C#3
________ ________ ________
0.000 0.000 0.000
TECHNICAL 8 OUTPUT
TECHNICAL 8 OUTPUT FOR REPLICATION 1
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.30652569D+04 0.0000000 0.0000000 EM
2 -0.30572773D+04 7.9796746 0.0026033 EM
3 -0.30561993D+04 1.0779747 0.0003526 EM
4 -0.30557023D+04 0.4970284 0.0001626 EM
5 -0.30554219D+04 0.2803728 0.0000918 EM
6 -0.30552540D+04 0.1679298 0.0000550 EM
7 -0.30551504D+04 0.1035349 0.0000339 EM
8 -0.30550852D+04 0.0651983 0.0000213 EM
9 -0.30550435D+04 0.0417617 0.0000137 EM
10 -0.30550164D+04 0.0271152 0.0000089 EM
11 -0.30549986D+04 0.0177893 0.0000058 EM
12 -0.30549868D+04 0.0117628 0.0000039 EM
13 -0.30549790D+04 0.0078213 0.0000026 EM
14 -0.30549738D+04 0.0052221 0.0000017 EM
15 -0.30549703D+04 0.0034971 0.0000011 EM
16 -0.30549679D+04 0.0023467 0.0000008 EM
17 -0.30549663D+04 0.0015773 0.0000005 EM
18 -0.30549653D+04 0.0010613 0.0000003 EM
19 -0.30549646D+04 0.0007148 0.0000002 EM
20 -0.30549641D+04 0.0004817 0.0000002 EM
21 -0.30549638D+04 0.0003248 0.0000001 EM
22 -0.30549635D+04 0.0002191 0.0000001 EM
23 -0.30549634D+04 0.0001478 0.0000000 EM
24 -0.30549633D+04 0.0000998 0.0000000 EM
25 -0.30549632D+04 0.0000674 0.0000000 EM
26 -0.30549632D+04 0.0000455 0.0000000 EM
27 -0.30549631D+04 0.0000307 0.0000000 EM
28 -0.30549631D+04 0.0000207 0.0000000 EM
29 -0.30549631D+04 0.0000140 0.0000000 EM
30 -0.30549631D+04 0.0000094 0.0000000 EM
31 -0.30549631D+04 0.0000064 0.0000000 EM
32 -0.30549631D+04 0.0000043 0.0000000 EM
33 -0.30549631D+04 0.0000029 0.0000000 EM
34 -0.30549631D+04 0.0000020 0.0000000 EM
35 -0.30549631D+04 0.0000013 0.0000000 EM
36 -0.30549631D+04 0.0000024 0.0000000 FS
37 -0.30549631D+04 0.0000003 0.0000000 FS
38 -0.30549631D+04 0.0000000 0.0000000 FS
39 -0.30549631D+04 0.0000000 0.0000000 EM
40 -0.30549631D+04 0.0000000 0.0000000 EM
TECHNICAL 9 OUTPUT
Error messages for each replication (if any)
SAVEDATA INFORMATION
Order of variables
Y1
Y2
Y3
Y4
C
Save file
ex7.22.dat
Save file format Free
Save file record length 10000
Beginning Time: 22:24:33
Ending Time: 22:24:33
Elapsed Time: 00:00:00
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