Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 11:12 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a LCA with
continuous latent class indicators using
user-specified starting values without
random starts
DATA: FILE IS ex7.10.dat;
VARIABLE: NAMES ARE y1-y4 c;
USEVARIABLES ARE y1-y4;
CLASSES = c (2);
ANALYSIS: TYPE = MIXTURE;
STARTS = 0;
MODEL:
%OVERALL%
%c#1%
[y1-y4*1];
y1-y4;
%c#2%
[y1-y4*-1];
y1-y4;
OUTPUT: TECH1 TECH8;
*** WARNING in MODEL command
All variables are uncorrelated with all other variables within class.
Check that this is what is intended.
1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS
this is an example of a LCA with
continuous latent class indicators using
user-specified starting values without
random starts
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 500
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
Input data file(s)
ex7.10.dat
Input data format FREE
UNIVARIATE SAMPLE STATISTICS
UNIVARIATE HIGHER-ORDER MOMENT DESCRIPTIVE STATISTICS
Variable/ Mean/ Skewness/ Minimum/ % with Percentiles
Sample Size Variance Kurtosis Maximum Min/Max 20%/60% 40%/80% Median
Y1 0.035 0.025 -4.054 0.20% -1.335 -0.421 -0.003
500.000 2.228 -0.495 3.914 0.20% 0.495 1.443
Y2 0.002 0.014 -3.629 0.20% -1.287 -0.344 0.035
500.000 2.066 -0.608 3.515 0.20% 0.396 1.328
Y3 -0.001 0.086 -4.511 0.20% -1.246 -0.423 -0.057
500.000 1.808 -0.283 3.810 0.20% 0.284 1.196
Y4 -0.012 -0.114 -3.505 0.20% -1.380 -0.358 0.037
500.000 2.080 -0.590 3.539 0.20% 0.442 1.206
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 17
Loglikelihood
H0 Value -3174.564
H0 Scaling Correction Factor 0.9595
for MLR
Information Criteria
Akaike (AIC) 6383.127
Bayesian (BIC) 6454.776
Sample-Size Adjusted BIC 6400.817
(n* = (n + 2) / 24)
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THE ESTIMATED MODEL
Latent
Classes
1 260.17579 0.52035
2 239.82421 0.47965
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON ESTIMATED POSTERIOR PROBABILITIES
Latent
Classes
1 260.17579 0.52035
2 239.82421 0.47965
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES
BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP
Class Counts and Proportions
Latent
Classes
1 261 0.52200
2 239 0.47800
CLASSIFICATION QUALITY
Entropy 0.909
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1 2
1 0.975 0.025
2 0.024 0.976
Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)
1 2
1 0.978 0.022
2 0.027 0.973
Logits for the Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)
1 2
1 3.796 0.000
2 -3.574 0.000
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
Latent Class 1
Means
Y1 1.040 0.071 14.744 0.000
Y2 1.006 0.064 15.781 0.000
Y3 0.867 0.068 12.771 0.000
Y4 0.980 0.060 16.201 0.000
Variances
Y1 1.154 0.100 11.513 0.000
Y2 0.979 0.079 12.387 0.000
Y3 1.085 0.087 12.488 0.000
Y4 0.909 0.077 11.741 0.000
Latent Class 2
Means
Y1 -1.055 0.070 -15.035 0.000
Y2 -1.087 0.067 -16.140 0.000
Y3 -0.942 0.063 -15.062 0.000
Y4 -1.089 0.075 -14.605 0.000
Variances
Y1 1.110 0.101 10.970 0.000
Y2 0.965 0.098 9.878 0.000
Y3 0.888 0.090 9.876 0.000
Y4 1.124 0.103 10.900 0.000
Categorical Latent Variables
Means
C#1 0.081 0.095 0.853 0.393
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.179E+00
(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 0 6
Y3 0 0 7
Y4 0 0 0 8
PARAMETER SPECIFICATION FOR LATENT CLASS 2
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
9 10 11 12
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 13
Y2 0 14
Y3 0 0 15
Y4 0 0 0 16
PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C#1 C#2
________ ________
17 0
STARTING VALUES FOR LATENT CLASS 1
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
1.000 1.000 1.000 1.000
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.114
Y2 0.000 1.033
Y3 0.000 0.000 0.904
Y4 0.000 0.000 0.000 1.040
STARTING VALUES FOR LATENT CLASS 2
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
-1.000 -1.000 -1.000 -1.000
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 1.114
Y2 0.000 1.033
Y3 0.000 0.000 0.904
Y4 0.000 0.000 0.000 1.040
STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
C#1 C#2
________ ________
0.000 0.000
TECHNICAL 8 OUTPUT
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.31831778D+04 0.0000000 0.0000000 EM
2 -0.31748131D+04 8.3646798 0.0026278 EM
3 -0.31746072D+04 0.2059063 0.0000649 EM
4 -0.31745735D+04 0.0336986 0.0000106 EM
5 -0.31745660D+04 0.0075237 0.0000024 EM
6 -0.31745643D+04 0.0017591 0.0000006 EM
7 -0.31745638D+04 0.0004155 0.0000001 EM
8 -0.31745637D+04 0.0000983 0.0000000 EM
9 -0.31745637D+04 0.0000234 0.0000000 EM
10 -0.31745637D+04 0.0000056 0.0000000 EM
11 -0.31745637D+04 0.0000013 0.0000000 EM
12 -0.31745637D+04 0.0000003 0.0000000 EM
13 -0.31745637D+04 0.0000001 0.0000000 EM
14 -0.31745637D+04 0.0000000 0.0000000 EM
Beginning Time: 23:12:55
Ending Time: 23:12:55
Elapsed Time: 00:00:00
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