Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 10:24 PM
INPUT INSTRUCTIONS
title: this is an example of a hidden Markov
model with four time points
montecarlo:
names are u1-u4;
generate = u1-u4(1);
categorical = u1-u4;
genclasses = c1(2) c2(2) c3(2) c4(2);
classes = c1(2) c2(2) c3(2) c4(2);
nobs = 5000;
seed = 3454367;
nrep = 1;
save = ex8.12.dat;
analysis:
type = mixture;
model population:
%overall%
[c2#1-c4#1*0] (4);
c4#1 on c3#1*2 (3);
c3#1 on c2#1*2 (3);
c2#1 on c1#1*2 (3);
model population-c1:
%c1#1%
[u1$1*1] (1);
%c1#2%
[u1$1*-1] (2);
model population-c2:
%c2#1%
[u2$1*1] (1);
%c2#2%
[u2$1*-1] (2);
model population-c3:
%c3#1%
[u3$1*1] (1);
%c3#2%
[u3$1*-1] (2);
model population-c4:
%c4#1%
[u4$1*1] (1);
%c4#2%
[u4$1*-1] (2);
model:
%overall%
[c2#1-c4#1*0] (4);
c4#1 on c3#1*2 (3);
c3#1 on c2#1*2 (3);
c2#1 on c1#1*2 (3);
model c1:
%c1#1%
[u1$1*1] (1);
%c1#2%
[u1$1*-1] (2);
model c2:
%c2#1%
[u2$1*1] (1);
%c2#2%
[u2$1*-1] (2);
model c3:
%c3#1%
[u3$1*1] (1);
%c3#2%
[u3$1*-1] (2);
model c4:
%c4#1%
[u4$1*1] (1);
%c4#2%
[u4$1*-1] (2);
output:
tech8 tech9;
INPUT READING TERMINATED NORMALLY
this is an example of a hidden Markov
model with four time points
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 5000
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 4
Observed dependent variables
Binary and ordered categorical (ordinal)
U1 U2 U3 U4
Categorical latent variables
C1 C2 C3 C4
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-03
Relative loglikelihood change 0.100D-05
Derivative 0.100D-03
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-03
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-03
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
Parameterization LOGIT
Link LOGIT
MODEL FIT INFORMATION
Number of Free Parameters 5
Loglikelihood
H0 Value
Mean -13427.811
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 -13427.811 -13427.811
0.980 0.000 -13427.811 -13427.811
0.950 0.000 -13427.811 -13427.811
0.900 0.000 -13427.811 -13427.811
0.800 0.000 -13427.811 -13427.811
0.700 0.000 -13427.811 -13427.811
0.500 0.000 -13427.811 -13427.811
0.300 0.000 -13427.811 -13427.811
0.200 0.000 -13427.811 -13427.811
0.100 0.000 -13427.811 -13427.811
0.050 0.000 -13427.811 -13427.811
0.020 0.000 -13427.811 -13427.811
0.010 0.000 -13427.811 -13427.811
Information Criteria
Akaike (AIC)
Mean 26865.623
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 26865.623 26865.623
0.980 0.000 26865.623 26865.623
0.950 0.000 26865.623 26865.623
0.900 0.000 26865.623 26865.623
0.800 0.000 26865.623 26865.623
0.700 0.000 26865.623 26865.623
0.500 0.000 26865.623 26865.623
0.300 0.000 26865.623 26865.623
0.200 0.000 26865.623 26865.623
0.100 0.000 26865.623 26865.623
0.050 0.000 26865.623 26865.623
0.020 0.000 26865.623 26865.623
0.010 0.000 26865.623 26865.623
Bayesian (BIC)
Mean 26898.209
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 26898.209 26898.209
0.980 0.000 26898.209 26898.209
0.950 0.000 26898.209 26898.209
0.900 0.000 26898.209 26898.209
0.800 0.000 26898.209 26898.209
0.700 0.000 26898.209 26898.209
0.500 0.000 26898.209 26898.209
0.300 0.000 26898.209 26898.209
0.200 0.000 26898.209 26898.209
0.100 0.000 26898.209 26898.209
0.050 0.000 26898.209 26898.209
0.020 0.000 26898.209 26898.209
0.010 0.000 26898.209 26898.209
Sample-Size Adjusted BIC (n* = (n + 2) / 24)
Mean 26882.320
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 26882.320 26882.320
0.980 0.000 26882.320 26882.320
0.950 0.000 26882.320 26882.320
0.900 0.000 26882.320 26882.320
0.800 0.000 26882.320 26882.320
0.700 0.000 26882.320 26882.320
0.500 0.000 26882.320 26882.320
0.300 0.000 26882.320 26882.320
0.200 0.000 26882.320 26882.320
0.100 0.000 26882.320 26882.320
0.050 0.000 26882.320 26882.320
0.020 0.000 26882.320 26882.320
0.010 0.000 26882.320 26882.320
Chi-Square Test of Model Fit for the Binary and Ordered Categorical
(Ordinal) Outcomes
Pearson Chi-Square
Mean 10.297
Std Dev 0.000
Degrees of freedom 10
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 1.000 2.558 10.297
0.980 1.000 3.059 10.297
0.950 1.000 3.940 10.297
0.900 1.000 4.865 10.297
0.800 1.000 6.179 10.297
0.700 1.000 7.267 10.297
0.500 1.000 9.342 10.297
0.300 0.000 11.781 10.297
0.200 0.000 13.442 10.297
0.100 0.000 15.987 10.297
0.050 0.000 18.307 10.297
0.020 0.000 21.161 10.297
0.010 0.000 23.209 10.297
Likelihood Ratio Chi-Square
Mean 10.240
Std Dev 0.000
Degrees of freedom 10
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 1.000 2.558 10.240
0.980 1.000 3.059 10.240
0.950 1.000 3.940 10.240
0.900 1.000 4.865 10.240
0.800 1.000 6.179 10.240
0.700 1.000 7.267 10.240
0.500 1.000 9.342 10.240
0.300 0.000 11.781 10.240
0.200 0.000 13.442 10.240
0.100 0.000 15.987 10.240
0.050 0.000 18.307 10.240
0.020 0.000 21.161 10.240
0.010 0.000 23.209 10.240
MODEL RESULTS USE THE LATENT CLASS VARIABLE ORDER
C1 C2 C3 C4
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS
BASED ON THE ESTIMATED MODEL
Latent Class
Pattern
1 1 1 1 1761.53918 0.35231
1 1 1 2 180.91687 0.03618
1 1 2 1 95.11212 0.01902
1 1 2 2 104.38560 0.02088
1 2 1 1 95.11212 0.01902
1 2 1 2 9.76838 0.00195
1 2 2 1 54.87789 0.01098
1 2 2 2 60.22852 0.01205
2 1 1 1 1034.34326 0.20687
2 1 1 2 106.23104 0.02125
2 1 2 1 55.84808 0.01117
2 1 2 2 61.29330 0.01226
2 2 1 1 596.79647 0.11936
2 2 1 2 61.29330 0.01226
2 2 2 1 344.34026 0.06887
2 2 2 2 377.91362 0.07558
FINAL CLASS COUNTS AND PROPORTIONS FOR EACH LATENT CLASS VARIABLE
BASED ON THE ESTIMATED MODEL
Latent Class
Variable Class
C1 1 2361.94043 0.47239
2 2638.05933 0.52761
C2 1 3399.66919 0.67993
2 1600.33044 0.32007
C3 1 3846.00024 0.76920
2 1153.99939 0.23080
C4 1 4037.96924 0.80759
2 962.03058 0.19241
LATENT TRANSITION PROBABILITIES BASED ON THE ESTIMATED MODEL
C1 Classes (Rows) by C2 Classes (Columns)
1 2
1 0.907 0.093
2 0.477 0.523
C2 Classes (Rows) by C3 Classes (Columns)
1 2
1 0.907 0.093
2 0.477 0.523
C3 Classes (Rows) by C4 Classes (Columns)
1 2
1 0.907 0.093
2 0.477 0.523
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS
BASED ON ESTIMATED POSTERIOR PROBABILITIES
Latent Class
Pattern
1 1 1 1 1763.19932 0.35264
1 1 1 2 179.54575 0.03591
1 1 2 1 96.17338 0.01923
1 1 2 2 103.59851 0.02072
1 2 1 1 94.41003 0.01888
1 2 1 2 9.69407 0.00194
1 2 2 1 55.32552 0.01107
1 2 2 2 59.99624 0.01200
2 1 1 1 1037.80057 0.20756
2 1 1 2 107.86984 0.02157
2 1 2 1 55.79403 0.01116
2 1 2 2 62.09520 0.01242
2 2 1 1 590.41248 0.11808
2 2 1 2 61.04690 0.01221
2 2 2 1 342.35210 0.06847
2 2 2 2 380.68605 0.07614
FINAL CLASS COUNTS AND PROPORTIONS FOR EACH LATENT CLASS VARIABLE
BASED ON ESTIMATED POSTERIOR PROBABILITIES
Latent Class
Variable Class
C1 1 2361.94287 0.47239
2 2638.05713 0.52761
C2 1 3406.07666 0.68122
2 1593.92334 0.31878
C3 1 3843.97925 0.76880
2 1156.02112 0.23120
C4 1 4035.46753 0.80709
2 964.53253 0.19291
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS
BASED ON THEIR MOST LIKELY LATENT CLASS PATTERN
Class Counts and Proportions
Latent Class
Pattern
1 1 1 1 2301 0.46020
1 1 1 2 0 0.00000
1 1 2 1 0 0.00000
1 1 2 2 0 0.00000
1 2 1 1 0 0.00000
1 2 1 2 0 0.00000
1 2 2 1 0 0.00000
1 2 2 2 0 0.00000
2 1 1 1 1404 0.28080
2 1 1 2 0 0.00000
2 1 2 1 0 0.00000
2 1 2 2 0 0.00000
2 2 1 1 633 0.12660
2 2 1 2 0 0.00000
2 2 2 1 279 0.05580
2 2 2 2 383 0.07660
FINAL CLASS COUNTS AND PROPORTIONS FOR EACH LATENT CLASS VARIABLE
BASED ON THEIR MOST LIKELY LATENT CLASS PATTERN
Latent Class
Variable Class
C1 1 2301 0.46020
2 2699 0.53980
C2 1 3705 0.74100
2 1295 0.25900
C3 1 4338 0.86760
2 662 0.13240
C4 1 4617 0.92340
2 383 0.07660
CLASSIFICATION QUALITY
Entropy 0.374
MODEL RESULTS
ESTIMATES S. E. M. S. E. 95% % Sig
Population Average Std. Dev. Average Cover Coeff
Parameters for Class-specific Model Parts of C1
Latent Class C1#1
Thresholds
U1$1 1.000 0.9335 0.0000 0.1535 0.0044 1.000 1.000
Latent Class C1#2
Thresholds
U1$1 -1.000 -0.9039 0.0000 0.2693 0.0092 1.000 1.000
Parameters for Class-specific Model Parts of C2
Latent Class C2#1
Thresholds
U2$1 1.000 0.9335 0.0000 0.1535 0.0044 1.000 1.000
Latent Class C2#2
Thresholds
U2$1 -1.000 -0.9039 0.0000 0.2693 0.0092 1.000 1.000
Parameters for Class-specific Model Parts of C3
Latent Class C3#1
Thresholds
U3$1 1.000 0.9335 0.0000 0.1535 0.0044 1.000 1.000
Latent Class C3#2
Thresholds
U3$1 -1.000 -0.9039 0.0000 0.2693 0.0092 1.000 1.000
Parameters for Class-specific Model Parts of C4
Latent Class C4#1
Thresholds
U4$1 1.000 0.9335 0.0000 0.1535 0.0044 1.000 1.000
Latent Class C4#2
Thresholds
U4$1 -1.000 -0.9039 0.0000 0.2693 0.0092 1.000 1.000
Categorical Latent Variables
C4#1 ON
C3#1 2.000 2.3689 0.0000 0.6528 0.1361 1.000 1.000
C3#1 ON
C2#1 2.000 2.3689 0.0000 0.6528 0.1361 1.000 1.000
C2#1 ON
C1#1 2.000 2.3689 0.0000 0.6528 0.1361 1.000 1.000
Means
C1#1 0.000 -0.1106 0.0000 0.3600 0.0122 1.000 0.000
C2#1 0.000 -0.0930 0.0000 0.2297 0.0087 1.000 0.000
C3#1 0.000 -0.0930 0.0000 0.2297 0.0087 1.000 0.000
C4#1 0.000 -0.0930 0.0000 0.2297 0.0087 1.000 0.000
QUALITY OF NUMERICAL RESULTS
Average Condition Number for the Information Matrix 0.115E-02
(ratio of smallest to largest eigenvalue)
C-SPECIFIC CLASSIFICATION RESULTS
Classification Quality for C1
Entropy 0.163
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1 2
1 0.703 0.297
2 0.276 0.724
Classification Quality for C2
Entropy 0.262
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1 2
1 0.791 0.209
2 0.366 0.634
Classification Quality for C3
Entropy 0.362
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1 2
1 0.825 0.175
2 0.401 0.599
Classification Quality for C4
Entropy 0.402
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1 2
1 0.837 0.163
2 0.445 0.555
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 1 1 1
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 1 1 2
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 1 2 1
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 1 2 2
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 2 1 1
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 2 1 2
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 2 2 1
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 2 2 2
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 1 1 1
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 1 1 2
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 1 2 1
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 1 2 2
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 2 1 1
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 2 1 2
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 2 2 1
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 2 2 2
PARAMETER SPECIFICATION FOR LATENT CLASS INDICATOR MODEL PART
TAU(U) FOR LATENT CLASS PATTERN 1 1 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1 1 1 1
TAU(U) FOR LATENT CLASS PATTERN 1 1 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1 1 1 2
TAU(U) FOR LATENT CLASS PATTERN 1 1 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1 1 2 1
TAU(U) FOR LATENT CLASS PATTERN 1 1 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1 1 2 2
TAU(U) FOR LATENT CLASS PATTERN 1 2 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1 2 1 1
TAU(U) FOR LATENT CLASS PATTERN 1 2 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1 2 1 2
TAU(U) FOR LATENT CLASS PATTERN 1 2 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1 2 2 1
TAU(U) FOR LATENT CLASS PATTERN 1 2 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1 2 2 2
TAU(U) FOR LATENT CLASS PATTERN 2 1 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
2 1 1 1
TAU(U) FOR LATENT CLASS PATTERN 2 1 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
2 1 1 2
TAU(U) FOR LATENT CLASS PATTERN 2 1 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
2 1 2 1
TAU(U) FOR LATENT CLASS PATTERN 2 1 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
2 1 2 2
TAU(U) FOR LATENT CLASS PATTERN 2 2 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
2 2 1 1
TAU(U) FOR LATENT CLASS PATTERN 2 2 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
2 2 1 2
TAU(U) FOR LATENT CLASS PATTERN 2 2 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
2 2 2 1
TAU(U) FOR LATENT CLASS PATTERN 2 2 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
2 2 2 2
PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C1#1 C1#2 C2#1 C2#2 C3#1
________ ________ ________ ________ ________
3 0 4 0 4
ALPHA(C)
C3#2 C4#1 C4#2
________ ________ ________
0 4 0
BETA(C)
C3#1 C3#2
________ ________
C4#1 5 0
C4#2 0 0
BETA(C)
C2#1 C2#2
________ ________
C3#1 5 0
C3#2 0 0
BETA(C)
C1#1 C1#2
________ ________
C2#1 5 0
C2#2 0 0
STARTING VALUES FOR LATENT CLASS PATTERN 1 1 1 1
STARTING VALUES FOR LATENT CLASS PATTERN 1 1 1 2
STARTING VALUES FOR LATENT CLASS PATTERN 1 1 2 1
STARTING VALUES FOR LATENT CLASS PATTERN 1 1 2 2
STARTING VALUES FOR LATENT CLASS PATTERN 1 2 1 1
STARTING VALUES FOR LATENT CLASS PATTERN 1 2 1 2
STARTING VALUES FOR LATENT CLASS PATTERN 1 2 2 1
STARTING VALUES FOR LATENT CLASS PATTERN 1 2 2 2
STARTING VALUES FOR LATENT CLASS PATTERN 2 1 1 1
STARTING VALUES FOR LATENT CLASS PATTERN 2 1 1 2
STARTING VALUES FOR LATENT CLASS PATTERN 2 1 2 1
STARTING VALUES FOR LATENT CLASS PATTERN 2 1 2 2
STARTING VALUES FOR LATENT CLASS PATTERN 2 2 1 1
STARTING VALUES FOR LATENT CLASS PATTERN 2 2 1 2
STARTING VALUES FOR LATENT CLASS PATTERN 2 2 2 1
STARTING VALUES FOR LATENT CLASS PATTERN 2 2 2 2
STARTING VALUES FOR LATENT CLASS INDICATOR MODEL PART
TAU(U) FOR LATENT CLASS PATTERN 1 1 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 1 1 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 1.000 1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 1 1 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 1.000 -1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 1 1 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 1.000 -1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 -1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 -1.000 1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 -1.000 -1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 -1.000 -1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 1.000 1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 1.000 -1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 1.000 -1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 -1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 -1.000 1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 -1.000 -1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 -1.000 -1.000 -1.000
STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C1#1 C1#2 C2#1 C2#2 C3#1
________ ________ ________ ________ ________
0.000 0.000 0.000 0.000 0.000
ALPHA(C)
C3#2 C4#1 C4#2
________ ________ ________
0.000 0.000 0.000
BETA(C)
C3#1 C3#2
________ ________
C4#1 2.000 0.000
C4#2 0.000 0.000
BETA(C)
C2#1 C2#2
________ ________
C3#1 2.000 0.000
C3#2 0.000 0.000
BETA(C)
C1#1 C1#2
________ ________
C2#1 2.000 0.000
C2#2 0.000 0.000
POPULATION VALUES FOR LATENT CLASS PATTERN 1 1 1 1
POPULATION VALUES FOR LATENT CLASS PATTERN 1 1 1 2
POPULATION VALUES FOR LATENT CLASS PATTERN 1 1 2 1
POPULATION VALUES FOR LATENT CLASS PATTERN 1 1 2 2
POPULATION VALUES FOR LATENT CLASS PATTERN 1 2 1 1
POPULATION VALUES FOR LATENT CLASS PATTERN 1 2 1 2
POPULATION VALUES FOR LATENT CLASS PATTERN 1 2 2 1
POPULATION VALUES FOR LATENT CLASS PATTERN 1 2 2 2
POPULATION VALUES FOR LATENT CLASS PATTERN 2 1 1 1
POPULATION VALUES FOR LATENT CLASS PATTERN 2 1 1 2
POPULATION VALUES FOR LATENT CLASS PATTERN 2 1 2 1
POPULATION VALUES FOR LATENT CLASS PATTERN 2 1 2 2
POPULATION VALUES FOR LATENT CLASS PATTERN 2 2 1 1
POPULATION VALUES FOR LATENT CLASS PATTERN 2 2 1 2
POPULATION VALUES FOR LATENT CLASS PATTERN 2 2 2 1
POPULATION VALUES FOR LATENT CLASS PATTERN 2 2 2 2
POPULATION VALUES FOR LATENT CLASS INDICATOR MODEL PART
TAU(U) FOR LATENT CLASS PATTERN 1 1 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 1 1 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 1.000 1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 1 1 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 1.000 -1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 1 1 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 1.000 -1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 -1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 -1.000 1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 -1.000 -1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
1.000 -1.000 -1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 1.000 1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 1.000 -1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 1.000 -1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2 1 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 -1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2 1 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 -1.000 1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2 2 1
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 -1.000 -1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2 2 2
U1$1 U2$1 U3$1 U4$1
________ ________ ________ ________
-1.000 -1.000 -1.000 -1.000
POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C1#1 C1#2 C2#1 C2#2 C3#1
________ ________ ________ ________ ________
0.000 0.000 0.000 0.000 0.000
ALPHA(C)
C3#2 C4#1 C4#2
________ ________ ________
0.000 0.000 0.000
BETA(C)
C3#1 C3#2
________ ________
C4#1 2.000 0.000
C4#2 0.000 0.000
BETA(C)
C2#1 C2#2
________ ________
C3#1 2.000 0.000
C3#2 0.000 0.000
BETA(C)
C1#1 C1#2
________ ________
C2#1 2.000 0.000
C2#2 0.000 0.000
TECHNICAL 8 OUTPUT
TECHNICAL 8 OUTPUT FOR REPLICATION 1
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.13429257D+05 0.0000000 0.0000000 EM
2 -0.13428347D+05 0.9100962 0.0000678 EM
3 -0.13428256D+05 0.0915889 0.0000068 EM
4 -0.13428200D+05 0.0555921 0.0000041 EM
5 -0.13428165D+05 0.0344988 0.0000026 EM
6 -0.13428143D+05 0.0221289 0.0000016 EM
7 -0.13428129D+05 0.0148415 0.0000011 EM
8 -0.13428118D+05 0.0105094 0.0000008 EM
9 -0.13428110D+05 0.0078982 0.0000006 EM
10 -0.13428104D+05 0.0062936 0.0000005 EM
11 -0.13428099D+05 0.0052826 0.0000004 EM
12 -0.13428094D+05 0.0046259 0.0000003 EM
13 -0.13428090D+05 0.0041841 0.0000003 EM
14 -0.13428086D+05 0.0038754 0.0000003 EM
15 -0.13428082D+05 0.0036511 0.0000003 EM
16 -0.13428079D+05 0.0034818 0.0000003 EM
17 -0.13428075D+05 0.0033494 0.0000002 EM
18 -0.13428072D+05 0.0032425 0.0000002 EM
19 -0.13428069D+05 0.0031538 0.0000002 EM
20 -0.13428066D+05 0.0030783 0.0000002 EM
21 -0.13428063D+05 0.0030127 0.0000002 EM
22 -0.13428060D+05 0.0029546 0.0000002 EM
23 -0.13428057D+05 0.0029023 0.0000002 EM
24 -0.13428054D+05 0.0028546 0.0000002 EM
25 -0.13428051D+05 0.0028105 0.0000002 EM
26 -0.13428049D+05 0.0027693 0.0000002 EM
27 -0.13428046D+05 0.0027305 0.0000002 EM
28 -0.13428043D+05 0.0026935 0.0000002 EM
29 -0.13428041D+05 0.0026582 0.0000002 EM
30 -0.13428038D+05 0.0026242 0.0000002 EM
31 -0.13428035D+05 0.0025913 0.0000002 EM
32 -0.13428033D+05 0.0025593 0.0000002 EM
33 -0.13428030D+05 0.0025281 0.0000002 EM
34 -0.13428028D+05 0.0024977 0.0000002 EM
35 -0.13427840D+05 0.1878315 0.0000140 FS
36 -0.13427812D+05 0.0283131 0.0000021 FS
37 -0.13427811D+05 0.0002466 0.0000000 FS
38 -0.13427811D+05 0.0000085 0.0000000 FS
TECHNICAL 9 OUTPUT
Error messages for each replication (if any)
SAVEDATA INFORMATION
Order of variables
U1
U2
U3
U4
C1
C2
C3
C4
Save file
ex8.12.dat
Save file format Free
Save file record length 10000
Beginning Time: 22:24:43
Ending Time: 22:24:44
Elapsed Time: 00:00:01
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