Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 10:24 PM
INPUT INSTRUCTIONS
title:
this is an example of a LCA with a second-
order factor (twin analysis)
montecarlo:
names are u11-u13 u21-u23;
genclasses = c1(2) c2(2);
classes = c1(2) c2(2);
generate = u11-u23(1);
categorical = u11-u23;
nobs = 5000;
seed = 3454367;
nrep = 1;
save = ex7.18.dat;
analysis:
type = mixture;
algo = int;
model population:
%overall%
f by u11@0;
[f@0];
f@1;
[c1#1*0 c2#1*0];
c1#1 c2#1 on f*1 (1);
model population-c1:
%c1#1%
[u11$1-u13$1*-1];
%c1#2%
[u11$1-u13$1*1];
model population-c2:
%c2#1%
[u21$1-u23$1*-1];
%c2#2%
[u21$1-u23$1*1];
model:
%overall%
f by u11@0;
[f@0];
f@1;
[c1#1*0 c2#1*0];
c1#1 c2#1 on f*1 (1);
model c1:
%c1#1%
[u11$1-u13$1*-1];
%c1#2%
[u11$1-u13$1*1];
model c2:
%c2#1%
[u21$1-u23$1*-1];
%c2#2%
[u21$1-u23$1*1];
output:
tech8 tech9;
INPUT READING TERMINATED NORMALLY
this is an example of a LCA with a second-
order factor (twin analysis)
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 6
Number of independent variables 0
Number of continuous latent variables 1
Number of categorical latent variables 2
Observed dependent variables
Binary and ordered categorical (ordinal)
U11 U12 U13 U21 U22 U23
Continuous latent variables
F
Categorical latent variables
C1 C2
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
Parameterization LOGIT
Link LOGIT
Cholesky ON
MODEL FIT INFORMATION
Number of Free Parameters 15
Loglikelihood
H0 Value
Mean -20142.956
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 -20142.956 -20142.956
0.980 0.000 -20142.956 -20142.956
0.950 0.000 -20142.956 -20142.956
0.900 0.000 -20142.956 -20142.956
0.800 0.000 -20142.956 -20142.956
0.700 0.000 -20142.956 -20142.956
0.500 0.000 -20142.956 -20142.956
0.300 0.000 -20142.956 -20142.956
0.200 0.000 -20142.956 -20142.956
0.100 0.000 -20142.956 -20142.956
0.050 0.000 -20142.956 -20142.956
0.020 0.000 -20142.956 -20142.956
0.010 0.000 -20142.956 -20142.956
Information Criteria
Akaike (AIC)
Mean 40315.911
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 40315.911 40315.911
0.980 0.000 40315.911 40315.911
0.950 0.000 40315.911 40315.911
0.900 0.000 40315.911 40315.911
0.800 0.000 40315.911 40315.911
0.700 0.000 40315.911 40315.911
0.500 0.000 40315.911 40315.911
0.300 0.000 40315.911 40315.911
0.200 0.000 40315.911 40315.911
0.100 0.000 40315.911 40315.911
0.050 0.000 40315.911 40315.911
0.020 0.000 40315.911 40315.911
0.010 0.000 40315.911 40315.911
Bayesian (BIC)
Mean 40413.669
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 40413.669 40413.669
0.980 0.000 40413.669 40413.669
0.950 0.000 40413.669 40413.669
0.900 0.000 40413.669 40413.669
0.800 0.000 40413.669 40413.669
0.700 0.000 40413.669 40413.669
0.500 0.000 40413.669 40413.669
0.300 0.000 40413.669 40413.669
0.200 0.000 40413.669 40413.669
0.100 0.000 40413.669 40413.669
0.050 0.000 40413.669 40413.669
0.020 0.000 40413.669 40413.669
0.010 0.000 40413.669 40413.669
Sample-Size Adjusted BIC (n* = (n + 2) / 24)
Mean 40366.004
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 40366.004 40366.004
0.980 0.000 40366.004 40366.004
0.950 0.000 40366.004 40366.004
0.900 0.000 40366.004 40366.004
0.800 0.000 40366.004 40366.004
0.700 0.000 40366.004 40366.004
0.500 0.000 40366.004 40366.004
0.300 0.000 40366.004 40366.004
0.200 0.000 40366.004 40366.004
0.100 0.000 40366.004 40366.004
0.050 0.000 40366.004 40366.004
0.020 0.000 40366.004 40366.004
0.010 0.000 40366.004 40366.004
Chi-Square Test of Model Fit for the Binary and Ordered Categorical
(Ordinal) Outcomes
Pearson Chi-Square
Mean 42.947
Std Dev 0.000
Degrees of freedom 48
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 1.000 28.177 42.947
0.980 1.000 30.080 42.947
0.950 1.000 33.098 42.947
0.900 1.000 35.949 42.947
0.800 1.000 39.621 42.947
0.700 1.000 42.420 42.947
0.500 0.000 47.335 42.947
0.300 0.000 52.616 42.947
0.200 0.000 55.993 42.947
0.100 0.000 60.907 42.947
0.050 0.000 65.171 42.947
0.020 0.000 70.197 42.947
0.010 0.000 73.683 42.947
Likelihood Ratio Chi-Square
Mean 43.600
Std Dev 0.000
Degrees of freedom 48
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 1.000 28.177 43.600
0.980 1.000 30.080 43.600
0.950 1.000 33.098 43.600
0.900 1.000 35.949 43.600
0.800 1.000 39.621 43.600
0.700 1.000 42.420 43.600
0.500 0.000 47.335 43.600
0.300 0.000 52.616 43.600
0.200 0.000 55.993 43.600
0.100 0.000 60.907 43.600
0.050 0.000 65.171 43.600
0.020 0.000 70.197 43.600
0.010 0.000 73.683 43.600
MODEL RESULTS USE THE LATENT CLASS VARIABLE ORDER
C1 C2
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS
BASED ON THE ESTIMATED MODEL
Latent Class
Pattern
1 1 1559.69489 0.31194
1 2 1004.83398 0.20097
2 1 1144.59972 0.22892
2 2 1290.87141 0.25817
FINAL CLASS COUNTS AND PROPORTIONS FOR EACH LATENT CLASS VARIABLE
BASED ON THE ESTIMATED MODEL
Latent Class
Variable Class
C1 1 2564.52881 0.51291
2 2435.47119 0.48709
C2 1 2704.29468 0.54086
2 2295.70532 0.45914
LATENT TRANSITION PROBABILITIES BASED ON THE ESTIMATED MODEL
C1 Classes (Rows) by C2 Classes (Columns)
1 2
1 0.601 0.399
2 0.478 0.522
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS
BASED ON ESTIMATED POSTERIOR PROBABILITIES
Latent Class
Pattern
1 1 1559.18736 0.31184
1 2 1005.11311 0.20102
2 1 1144.91641 0.22898
2 2 1290.78312 0.25816
FINAL CLASS COUNTS AND PROPORTIONS FOR EACH LATENT CLASS VARIABLE
BASED ON ESTIMATED POSTERIOR PROBABILITIES
Latent Class
Variable Class
C1 1 2564.30054 0.51286
2 2435.69946 0.48714
C2 1 2704.10376 0.54082
2 2295.89624 0.45918
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 1342 0.26840
1 2 1150 0.23000
2 1 1219 0.24380
2 2 1289 0.25780
FINAL CLASS COUNTS AND PROPORTIONS FOR EACH LATENT CLASS VARIABLE
BASED ON THEIR MOST LIKELY LATENT CLASS PATTERN
Latent Class
Variable Class
C1 1 2492 0.49840
2 2508 0.50160
C2 1 2561 0.51220
2 2439 0.48780
CLASSIFICATION QUALITY
Entropy 0.407
MODEL RESULTS
ESTIMATES S. E. M. S. E. 95% % Sig
Population Average Std. Dev. Average Cover Coeff
Parameters in the Overall Part of the Model (Parameters Equal in All of the Classes)
F BY
U11 0.000 0.0000 0.0000 0.0000 0.0000 1.000 0.000
Means
F 0.000 0.0000 0.0000 0.0000 0.0000 1.000 0.000
Variances
F 1.000 1.0000 0.0000 0.0000 0.0000 1.000 0.000
Parameters for Class-specific Model Parts of C1
Latent Class C1#1
Thresholds
U11$1 -1.000 -0.9627 0.0000 0.0998 0.0014 1.000 1.000
U12$1 -1.000 -0.9844 0.0000 0.1032 0.0002 1.000 1.000
U13$1 -1.000 -0.9426 0.0000 0.0977 0.0033 1.000 1.000
Latent Class C1#2
Thresholds
U11$1 1.000 1.0120 0.0000 0.1044 0.0001 1.000 1.000
U12$1 1.000 1.0804 0.0000 0.1105 0.0065 1.000 1.000
U13$1 1.000 1.0537 0.0000 0.1081 0.0029 1.000 1.000
Parameters for Class-specific Model Parts of C2
Latent Class C2#1
Thresholds
U21$1 -1.000 -0.9353 0.0000 0.0920 0.0042 1.000 1.000
U22$1 -1.000 -1.0347 0.0000 0.1055 0.0012 1.000 1.000
U23$1 -1.000 -0.9166 0.0000 0.0898 0.0069 1.000 1.000
Latent Class C2#2
Thresholds
U21$1 1.000 0.9921 0.0000 0.1031 0.0001 1.000 1.000
U22$1 1.000 1.2868 0.0000 0.1387 0.0822 0.000 1.000
U23$1 1.000 0.9761 0.0000 0.1021 0.0006 1.000 1.000
Categorical Latent Variables
C1#1 ON
F 1.000 0.8605 0.0000 0.1238 0.0195 1.000 1.000
C2#1 ON
F 1.000 0.8605 0.0000 0.1238 0.0195 1.000 1.000
Intercepts
C1#1 0.000 0.0597 0.0000 0.1553 0.0036 1.000 0.000
C2#1 0.000 0.1900 0.0000 0.1533 0.0361 1.000 0.000
QUALITY OF NUMERICAL RESULTS
Average Condition Number for the Information Matrix 0.222E-01
(ratio of smallest to largest eigenvalue)
C-SPECIFIC CLASSIFICATION RESULTS
Classification Quality for C1
Entropy 0.399
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1 2
1 0.837 0.163
2 0.191 0.809
Classification Quality for C2
Entropy 0.412
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1 2
1 0.857 0.143
2 0.209 0.791
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 1
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0 0 0 0 0
NU
U23
________
0
LAMBDA
F
________
U11 0
U12 0
U13 0
U21 0
U22 0
U23 0
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 0
U12 0 0
U13 0 0 0
U21 0 0 0 0
U22 0 0 0 0 0
U23 0 0 0 0 0
THETA
U23
________
U23 0
ALPHA
F
________
0
BETA
F
________
F 0
PSI
F
________
F 0
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 2
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0 0 0 0 0
NU
U23
________
0
LAMBDA
F
________
U11 0
U12 0
U13 0
U21 0
U22 0
U23 0
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 0
U12 0 0
U13 0 0 0
U21 0 0 0 0
U22 0 0 0 0 0
U23 0 0 0 0 0
THETA
U23
________
U23 0
ALPHA
F
________
0
BETA
F
________
F 0
PSI
F
________
F 0
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 1
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0 0 0 0 0
NU
U23
________
0
LAMBDA
F
________
U11 0
U12 0
U13 0
U21 0
U22 0
U23 0
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 0
U12 0 0
U13 0 0 0
U21 0 0 0 0
U22 0 0 0 0 0
U23 0 0 0 0 0
THETA
U23
________
U23 0
ALPHA
F
________
0
BETA
F
________
F 0
PSI
F
________
F 0
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 2
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0 0 0 0 0
NU
U23
________
0
LAMBDA
F
________
U11 0
U12 0
U13 0
U21 0
U22 0
U23 0
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 0
U12 0 0
U13 0 0 0
U21 0 0 0 0
U22 0 0 0 0 0
U23 0 0 0 0 0
THETA
U23
________
U23 0
ALPHA
F
________
0
BETA
F
________
F 0
PSI
F
________
F 0
PARAMETER SPECIFICATION FOR LATENT CLASS INDICATOR MODEL PART
TAU(U) FOR LATENT CLASS PATTERN 1 1
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
1 2 3 4 5
TAU(U) FOR LATENT CLASS PATTERN 1 1
U23$1
________
6
TAU(U) FOR LATENT CLASS PATTERN 1 2
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
1 2 3 7 8
TAU(U) FOR LATENT CLASS PATTERN 1 2
U23$1
________
9
TAU(U) FOR LATENT CLASS PATTERN 2 1
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
10 11 12 4 5
TAU(U) FOR LATENT CLASS PATTERN 2 1
U23$1
________
6
TAU(U) FOR LATENT CLASS PATTERN 2 2
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
10 11 12 7 8
TAU(U) FOR LATENT CLASS PATTERN 2 2
U23$1
________
9
PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C1#1 C1#2 C2#1 C2#2
________ ________ ________ ________
13 0 14 0
GAMMA(C)
F
________
C1#1 15
C1#2 0
C2#1 15
C2#2 0
STARTING VALUES FOR LATENT CLASS PATTERN 1 1
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0.000 0.000 0.000 0.000 0.000
NU
U23
________
0.000
LAMBDA
F
________
U11 0.000
U12 0.000
U13 0.000
U21 0.000
U22 0.000
U23 0.000
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 1.000
U12 0.000 1.000
U13 0.000 0.000 1.000
U21 0.000 0.000 0.000 1.000
U22 0.000 0.000 0.000 0.000 1.000
U23 0.000 0.000 0.000 0.000 0.000
THETA
U23
________
U23 1.000
ALPHA
F
________
0.000
BETA
F
________
F 0.000
PSI
F
________
F 1.000
STARTING VALUES FOR LATENT CLASS PATTERN 1 2
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0.000 0.000 0.000 0.000 0.000
NU
U23
________
0.000
LAMBDA
F
________
U11 0.000
U12 0.000
U13 0.000
U21 0.000
U22 0.000
U23 0.000
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 1.000
U12 0.000 1.000
U13 0.000 0.000 1.000
U21 0.000 0.000 0.000 1.000
U22 0.000 0.000 0.000 0.000 1.000
U23 0.000 0.000 0.000 0.000 0.000
THETA
U23
________
U23 1.000
ALPHA
F
________
0.000
BETA
F
________
F 0.000
PSI
F
________
F 1.000
STARTING VALUES FOR LATENT CLASS PATTERN 2 1
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0.000 0.000 0.000 0.000 0.000
NU
U23
________
0.000
LAMBDA
F
________
U11 0.000
U12 0.000
U13 0.000
U21 0.000
U22 0.000
U23 0.000
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 1.000
U12 0.000 1.000
U13 0.000 0.000 1.000
U21 0.000 0.000 0.000 1.000
U22 0.000 0.000 0.000 0.000 1.000
U23 0.000 0.000 0.000 0.000 0.000
THETA
U23
________
U23 1.000
ALPHA
F
________
0.000
BETA
F
________
F 0.000
PSI
F
________
F 1.000
STARTING VALUES FOR LATENT CLASS PATTERN 2 2
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0.000 0.000 0.000 0.000 0.000
NU
U23
________
0.000
LAMBDA
F
________
U11 0.000
U12 0.000
U13 0.000
U21 0.000
U22 0.000
U23 0.000
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 1.000
U12 0.000 1.000
U13 0.000 0.000 1.000
U21 0.000 0.000 0.000 1.000
U22 0.000 0.000 0.000 0.000 1.000
U23 0.000 0.000 0.000 0.000 0.000
THETA
U23
________
U23 1.000
ALPHA
F
________
0.000
BETA
F
________
F 0.000
PSI
F
________
F 1.000
STARTING VALUES FOR LATENT CLASS INDICATOR MODEL PART
TAU(U) FOR LATENT CLASS PATTERN 1 1
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
-1.000 -1.000 -1.000 -1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 1 1
U23$1
________
-1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
-1.000 -1.000 -1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2
U23$1
________
1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
1.000 1.000 1.000 -1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1
U23$1
________
-1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
1.000 1.000 1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2
U23$1
________
1.000
STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C1#1 C1#2 C2#1 C2#2
________ ________ ________ ________
0.000 0.000 0.000 0.000
GAMMA(C)
F
________
C1#1 1.000
C1#2 0.000
C2#1 1.000
C2#2 0.000
POPULATION VALUES FOR LATENT CLASS PATTERN 1 1
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0.000 0.000 0.000 0.000 0.000
NU
U23
________
0.000
LAMBDA
F
________
U11 0.000
U12 0.000
U13 0.000
U21 0.000
U22 0.000
U23 0.000
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 0.000
U12 0.000 0.000
U13 0.000 0.000 0.000
U21 0.000 0.000 0.000 0.000
U22 0.000 0.000 0.000 0.000 0.000
U23 0.000 0.000 0.000 0.000 0.000
THETA
U23
________
U23 0.000
ALPHA
F
________
0.000
BETA
F
________
F 0.000
PSI
F
________
F 1.000
POPULATION VALUES FOR LATENT CLASS PATTERN 1 2
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0.000 0.000 0.000 0.000 0.000
NU
U23
________
0.000
LAMBDA
F
________
U11 0.000
U12 0.000
U13 0.000
U21 0.000
U22 0.000
U23 0.000
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 0.000
U12 0.000 0.000
U13 0.000 0.000 0.000
U21 0.000 0.000 0.000 0.000
U22 0.000 0.000 0.000 0.000 0.000
U23 0.000 0.000 0.000 0.000 0.000
THETA
U23
________
U23 0.000
ALPHA
F
________
0.000
BETA
F
________
F 0.000
PSI
F
________
F 1.000
POPULATION VALUES FOR LATENT CLASS PATTERN 2 1
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0.000 0.000 0.000 0.000 0.000
NU
U23
________
0.000
LAMBDA
F
________
U11 0.000
U12 0.000
U13 0.000
U21 0.000
U22 0.000
U23 0.000
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 0.000
U12 0.000 0.000
U13 0.000 0.000 0.000
U21 0.000 0.000 0.000 0.000
U22 0.000 0.000 0.000 0.000 0.000
U23 0.000 0.000 0.000 0.000 0.000
THETA
U23
________
U23 0.000
ALPHA
F
________
0.000
BETA
F
________
F 0.000
PSI
F
________
F 1.000
POPULATION VALUES FOR LATENT CLASS PATTERN 2 2
NU
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
0.000 0.000 0.000 0.000 0.000
NU
U23
________
0.000
LAMBDA
F
________
U11 0.000
U12 0.000
U13 0.000
U21 0.000
U22 0.000
U23 0.000
THETA
U11 U12 U13 U21 U22
________ ________ ________ ________ ________
U11 0.000
U12 0.000 0.000
U13 0.000 0.000 0.000
U21 0.000 0.000 0.000 0.000
U22 0.000 0.000 0.000 0.000 0.000
U23 0.000 0.000 0.000 0.000 0.000
THETA
U23
________
U23 0.000
ALPHA
F
________
0.000
BETA
F
________
F 0.000
PSI
F
________
F 1.000
POPULATION VALUES FOR LATENT CLASS INDICATOR MODEL PART
TAU(U) FOR LATENT CLASS PATTERN 1 1
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
-1.000 -1.000 -1.000 -1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 1 1
U23$1
________
-1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
-1.000 -1.000 -1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 1 2
U23$1
________
1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
1.000 1.000 1.000 -1.000 -1.000
TAU(U) FOR LATENT CLASS PATTERN 2 1
U23$1
________
-1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2
U11$1 U12$1 U13$1 U21$1 U22$1
________ ________ ________ ________ ________
1.000 1.000 1.000 1.000 1.000
TAU(U) FOR LATENT CLASS PATTERN 2 2
U23$1
________
1.000
POPULATION VALUES FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C1#1 C1#2 C2#1 C2#2
________ ________ ________ ________
0.000 0.000 0.000 0.000
GAMMA(C)
F
________
C1#1 1.000
C1#2 0.000
C2#1 1.000
C2#2 0.000
TECHNICAL 8 OUTPUT
TECHNICAL 8 OUTPUT FOR REPLICATION 1
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.20150468D+05 0.0000000 0.0000000 EM
2 -0.20145955D+05 4.5126575 0.0002239 EM
3 -0.20145216D+05 0.7391764 0.0000367 EM
4 -0.20144748D+05 0.4683941 0.0000233 EM
5 -0.20144433D+05 0.3146529 0.0000156 EM
6 -0.20143011D+05 1.4224744 0.0000706 FS
7 -0.20142956D+05 0.0550399 0.0000027 FS
8 -0.20142956D+05 0.0001216 0.0000000 FS
TECHNICAL 9 OUTPUT
Error messages for each replication (if any)
SAVEDATA INFORMATION
Order of variables
U11
U12
U13
U21
U22
U23
C1
C2
Save file
ex7.18.dat
Save file format Free
Save file record length 10000
Beginning Time: 22:24:30
Ending Time: 22:24:30
Elapsed Time: 00:00:00
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