Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 11:13 PM
INPUT INSTRUCTIONS
TITLE: this is an example of mixture modeling
with known classes (multiple group
analysis)
DATA: FILE IS ex7.21.dat;
VARIABLE: NAMES = g y1-y4;
CLASSES = cg (2) c (2);
KNOWNCLASS = cg (g = 0 g = 1);
ANALYSIS: TYPE = MIXTURE;
MODEL:
%OVERALL%
c ON cg;
MODEL c:
%c#1%
[y1-y4];
%c#2%
[y1-y4];
MODEL cg:
%cg#1%
y1-y4;
%cg#2%
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 mixture modeling
with known classes (multiple group
analysis)
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 1000
Number of dependent variables 4
Number of independent variables 0
Number of continuous latent variables 0
Number of categorical latent variables 2
Observed dependent variables
Continuous
Y1 Y2 Y3 Y4
Categorical latent variables
CG C
Knownclass CG
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
Random Starts Specifications
Number of initial stage random starts 20
Number of final stage optimizations 4
Number of initial stage iterations 10
Initial stage convergence criterion 0.100D+01
Random starts scale 0.500D+01
Random seed for generating random starts 0
Parameterization LOGIT
Input data file(s)
ex7.21.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 -0.239 0.063 -4.054 0.10% -1.370 -0.612 -0.301
1000.000 1.628 -0.459 3.196 0.10% 0.070 0.924
Y2 -0.261 0.106 -3.834 0.10% -1.418 -0.661 -0.304
1000.000 1.542 -0.482 4.215 0.10% 0.052 0.877
Y3 -0.262 0.087 -4.511 0.10% -1.401 -0.743 -0.385
1000.000 1.689 -0.538 3.201 0.10% 0.083 0.918
Y4 -0.256 0.146 -3.351 0.10% -1.409 -0.777 -0.361
1000.000 1.704 -0.723 3.291 0.10% 0.066 1.040
RANDOM STARTS RESULTS RANKED FROM THE BEST TO THE WORST LOGLIKELIHOOD VALUES
Final stage loglikelihood values at local maxima, seeds, and initial stage start numbers:
-6273.830 285380 1
-6273.830 27071 15
-6273.830 573096 20
-6273.830 107446 12
THE BEST LOGLIKELIHOOD VALUE HAS BEEN REPLICATED. RERUN WITH AT LEAST TWICE THE
RANDOM STARTS TO CHECK THAT THE BEST LOGLIKELIHOOD IS STILL OBTAINED AND REPLICATED.
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 19
Loglikelihood
H0 Value -6273.830
H0 Scaling Correction Factor 0.9749
for MLR
Information Criteria
Akaike (AIC) 12585.660
Bayesian (BIC) 12678.907
Sample-Size Adjusted BIC 12618.562
(n* = (n + 2) / 24)
FINAL CLASS COUNTS AND PROPORTIONS FOR EACH LATENT CLASS VARIABLE
BASED ON THE ESTIMATED MODEL
Latent Class
Variable Class
CG 1 513.00000 0.51300
2 487.00000 0.48700
C 1 622.02063 0.62202
2 377.97937 0.37798
LATENT CLASS INDICATOR MEANS AND PROBABILITIES FOR EACH LATENT CLASS
MEAN/PROBABILITY PROFILES FOR C
Latent class
1 2
Y1 -0.960 0.938
Y2 -0.957 0.905
Y3 -1.010 0.970
Y4 -1.041 1.008
LATENT TRANSITION PROBABILITIES BASED ON THE ESTIMATED MODEL
CG Classes (Rows) by C Classes (Columns)
1 2
1 0.754 0.246
2 0.483 0.517
TRANSITION PROBABILITY ODDS
TRANSITION TABLE ODDS AND 95% CONFIDENCE INTERVALS FOR CG TO C
1.000(1.000,1.000) 0.326(0.264,0.401)
0.933(0.780,1.115) 1.000(1.000,1.000)
C-SPECIFIC CLASSIFICATION RESULTS
Classification Quality for CG
Entropy 1.000
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1 2
1 1.000 0.000
2 0.000 1.000
Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)
1 2
1 1.000 0.000
2 0.000 1.000
Logits for the Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)
1 2
1 13.816 0.000
2 -13.816 0.000
Classification Quality for C
Entropy 0.961
Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)
1 2
1 0.993 0.007
2 0.011 0.989
Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)
1 2
1 0.993 0.007
2 0.011 0.989
Logits for the Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)
1 2
1 4.975 0.000
2 -4.477 0.000
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
Parameters for Class-specific Model Parts of CG
Latent Class CG#1
Variances
Y1 1.021 0.066 15.466 0.000
Y2 0.986 0.065 15.246 0.000
Y3 0.990 0.063 15.824 0.000
Y4 1.001 0.060 16.601 0.000
Latent Class CG#2
Variances
Y1 0.551 0.035 15.642 0.000
Y2 0.447 0.027 16.534 0.000
Y3 0.514 0.031 16.337 0.000
Y4 0.465 0.030 15.428 0.000
Parameters for Class-specific Model Parts of C
Latent Class C#1
Means
Y1 -0.960 0.036 -26.726 0.000
Y2 -0.957 0.033 -28.712 0.000
Y3 -1.010 0.034 -29.435 0.000
Y4 -1.041 0.034 -30.998 0.000
Latent Class C#2
Means
Y1 0.938 0.042 22.595 0.000
Y2 0.905 0.039 23.449 0.000
Y3 0.970 0.041 23.425 0.000
Y4 1.008 0.040 25.270 0.000
Categorical Latent Variables
C#1 ON
CG#1 1.192 0.140 8.502 0.000
Means
CG#1 0.052 0.063 0.822 0.411
C#1 -0.070 0.091 -0.765 0.444
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.345E-01
(ratio of smallest to largest eigenvalue)
TECHNICAL 1 OUTPUT
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 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 PATTERN 1 2
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
9 10 11 12
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 5
Y2 0 6
Y3 0 0 7
Y4 0 0 0 8
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 1
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
1 2 3 4
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 13
Y2 0 14
Y3 0 0 15
Y4 0 0 0 16
PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 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)
CG#1 CG#2 C#1 C#2
________ ________ ________ ________
17 0 18 0
BETA(C)
CG#1 CG#2
________ ________
C#1 19 0
C#2 0 0
STARTING VALUES FOR LATENT CLASS PATTERN 1 1
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
-0.877 -0.882 -0.912 -0.908
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 0.814
Y2 0.000 0.771
Y3 0.000 0.000 0.844
Y4 0.000 0.000 0.000 0.852
STARTING VALUES FOR LATENT CLASS PATTERN 1 2
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
0.399 0.359 0.388 0.397
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 0.814
Y2 0.000 0.771
Y3 0.000 0.000 0.844
Y4 0.000 0.000 0.000 0.852
STARTING VALUES FOR LATENT CLASS PATTERN 2 1
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
-0.877 -0.882 -0.912 -0.908
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 0.814
Y2 0.000 0.771
Y3 0.000 0.000 0.844
Y4 0.000 0.000 0.000 0.852
STARTING VALUES FOR LATENT CLASS PATTERN 2 2
NU
Y1 Y2 Y3 Y4
________ ________ ________ ________
0.399 0.359 0.388 0.397
THETA
Y1 Y2 Y3 Y4
________ ________ ________ ________
Y1 0.814
Y2 0.000 0.771
Y3 0.000 0.000 0.844
Y4 0.000 0.000 0.000 0.852
STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART
ALPHA(C)
CG#1 CG#2 C#1 C#2
________ ________ ________ ________
0.000 0.000 0.000 0.000
BETA(C)
CG#1 CG#2
________ ________
C#1 0.000 0.000
C#2 0.000 0.000
TECHNICAL 8 OUTPUT
INITIAL STAGE ITERATIONS
TECHNICAL 8 OUTPUT FOR UNPERTURBED STARTING VALUE SET
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.67363796D+04 0.0000000 0.0000000 EM
2 -0.63000443D+04 436.3353227 0.0647730 EM
3 -0.62745672D+04 25.4771637 0.0040440 EM
4 -0.62738481D+04 0.7190546 0.0001146 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 1
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.11247895D+05 0.0000000 0.0000000 EM
2 -0.66505874D+04 4597.3080515 0.4087261 EM
3 -0.63209241D+04 329.6632402 0.0495690 EM
4 -0.62750152D+04 45.9089343 0.0072630 EM
5 -0.62738528D+04 1.1623940 0.0001852 EM
6 -0.62738304D+04 0.0224044 0.0000036 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 2
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.18887676D+05 0.0000000 0.0000000 EM
2 -0.73423781D+04 ************ 0.6112609 EM
3 -0.72229451D+04 119.4330277 0.0162663 EM
4 -0.70963279D+04 126.6172068 0.0175299 EM
5 -0.68892220D+04 207.1058322 0.0291849 EM
6 -0.65571616D+04 332.0604275 0.0482000 EM
7 -0.63069585D+04 250.2031156 0.0381572 EM
8 -0.62748289D+04 32.1295602 0.0050943 EM
9 -0.62738547D+04 0.9742502 0.0001553 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 3
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.16480211D+05 0.0000000 0.0000000 EM
2 -0.73879744D+04 9092.2367389 0.5517063 EM
3 -0.71448348D+04 243.1396133 0.0329102 EM
4 -0.67350642D+04 409.7705886 0.0573520 EM
5 -0.63555156D+04 379.5485636 0.0563541 EM
6 -0.62762511D+04 79.2645549 0.0124718 EM
7 -0.62738859D+04 2.3651817 0.0003768 EM
8 -0.62738313D+04 0.0545795 0.0000087 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 4
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.15452706D+05 0.0000000 0.0000000 EM
2 -0.73522180D+04 8100.4882367 0.5242116 EM
3 -0.72615122D+04 90.7058267 0.0123372 EM
4 -0.71510046D+04 110.5075563 0.0152183 EM
5 -0.69754198D+04 175.5848273 0.0245539 EM
6 -0.66797018D+04 295.7180355 0.0423943 EM
7 -0.63590578D+04 320.6439376 0.0480027 EM
8 -0.62773733D+04 81.6845710 0.0128454 EM
9 -0.62739185D+04 3.4548134 0.0005504 EM
10 -0.62738321D+04 0.0863407 0.0000138 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 5
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.11047689D+05 0.0000000 0.0000000 EM
2 -0.73633673D+04 3684.3215058 0.3334925 EM
3 -0.72959164D+04 67.4508718 0.0091603 EM
4 -0.72130966D+04 82.8198164 0.0113515 EM
5 -0.70853759D+04 127.7206801 0.0177068 EM
6 -0.68686503D+04 216.7256532 0.0305877 EM
7 -0.65308128D+04 337.8374340 0.0491854 EM
8 -0.63007376D+04 230.0752719 0.0352292 EM
9 -0.62746101D+04 26.1274634 0.0041467 EM
10 -0.62738490D+04 0.7610923 0.0001213 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 6
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.18258359D+05 0.0000000 0.0000000 EM
2 -0.66145625D+04 ************ 0.6377242 EM
3 -0.63292266D+04 285.3358446 0.0431375 EM
4 -0.62755410D+04 53.6856661 0.0084822 EM
5 -0.62738623D+04 1.6786232 0.0002675 EM
6 -0.62738306D+04 0.0317490 0.0000051 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 7
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.20833427D+05 0.0000000 0.0000000 EM
2 -0.69728021D+04 ************ 0.6653070 EM
3 -0.64870675D+04 485.7345941 0.0696613 EM
4 -0.62845589D+04 202.5086459 0.0312173 EM
5 -0.62741103D+04 10.4486084 0.0016626 EM
6 -0.62738372D+04 0.2730814 0.0000435 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 8
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.12063212D+05 0.0000000 0.0000000 EM
2 -0.69967767D+04 5066.4354633 0.4199906 EM
3 -0.65476949D+04 449.0817622 0.0641841 EM
4 -0.62906732D+04 257.0217079 0.0392538 EM
5 -0.62742465D+04 16.4267014 0.0026113 EM
6 -0.62738405D+04 0.4060477 0.0000647 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 9
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.19235086D+05 0.0000000 0.0000000 EM
2 -0.63873658D+04 ************ 0.6679315 EM
3 -0.62761982D+04 111.1675861 0.0174043 EM
4 -0.62738757D+04 2.3225109 0.0003701 EM
5 -0.62738310D+04 0.0447423 0.0000071 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 10
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.12302613D+05 0.0000000 0.0000000 EM
2 -0.72390453D+04 5063.5673215 0.4115847 EM
3 -0.69148631D+04 324.1822171 0.0447825 EM
4 -0.64716114D+04 443.2516976 0.0641013 EM
5 -0.62841805D+04 187.4309815 0.0289620 EM
6 -0.62740997D+04 10.0807236 0.0016041 EM
7 -0.62738369D+04 0.2627806 0.0000419 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 11
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.21933803D+05 0.0000000 0.0000000 EM
2 -0.63459081D+04 ************ 0.7106791 EM
3 -0.62761604D+04 69.7476400 0.0109910 EM
4 -0.62738785D+04 2.2818830 0.0003636 EM
5 -0.62738310D+04 0.0475774 0.0000076 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 12
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.12943657D+05 0.0000000 0.0000000 EM
2 -0.63194830D+04 6624.1735734 0.5117699 EM
3 -0.62749514D+04 44.5316313 0.0070467 EM
4 -0.62738496D+04 1.1017559 0.0001756 EM
5 -0.62738302D+04 0.0193840 0.0000031 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 13
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.17818315D+05 0.0000000 0.0000000 EM
2 -0.71850864D+04 ************ 0.5967584 EM
3 -0.69319881D+04 253.0983140 0.0352255 EM
4 -0.65979979D+04 333.9902002 0.0481810 EM
5 -0.63189277D+04 279.0702361 0.0422962 EM
6 -0.62752909D+04 43.6367847 0.0069057 EM
7 -0.62738670D+04 1.4239374 0.0002269 EM
8 -0.62738309D+04 0.0361012 0.0000058 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 14
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.25290132D+05 0.0000000 0.0000000 EM
2 -0.67199349D+04 ************ 0.7342863 EM
3 -0.63118822D+04 408.0527565 0.0607227 EM
4 -0.62748062D+04 37.0759504 0.0058740 EM
5 -0.62738554D+04 0.9508111 0.0001515 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 15
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.15304831D+05 0.0000000 0.0000000 EM
2 -0.64203360D+04 8884.4949154 0.5805027 EM
3 -0.62760483D+04 144.2877423 0.0224735 EM
4 -0.62738504D+04 2.1979054 0.0003502 EM
5 -0.62738301D+04 0.0202503 0.0000032 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 16
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.20047288D+05 0.0000000 0.0000000 EM
2 -0.74341164D+04 ************ 0.6291710 EM
3 -0.73352474D+04 98.8689891 0.0132994 EM
4 -0.71752101D+04 160.0373133 0.0218176 EM
5 -0.67671434D+04 408.0666909 0.0568717 EM
6 -0.63630291D+04 404.1143374 0.0597171 EM
7 -0.62767820D+04 86.2471501 0.0135544 EM
8 -0.62738993D+04 2.8826399 0.0004593 EM
9 -0.62738316D+04 0.0676777 0.0000108 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 17
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.18010562D+05 0.0000000 0.0000000 EM
2 -0.74088514D+04 ************ 0.5886385 EM
3 -0.73465521D+04 62.2993194 0.0084088 EM
4 -0.72553184D+04 91.2337010 0.0124186 EM
5 -0.69220105D+04 333.3078279 0.0459398 EM
6 -0.64637046D+04 458.3058749 0.0662099 EM
7 -0.62857584D+04 177.9462329 0.0275301 EM
8 -0.62741412D+04 11.6171825 0.0018482 EM
9 -0.62738379D+04 0.3033204 0.0000483 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 18
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.11010618D+05 0.0000000 0.0000000 EM
2 -0.71593606D+04 3851.2574155 0.3497767 EM
3 -0.67258524D+04 433.5082237 0.0605512 EM
4 -0.63364604D+04 389.3920129 0.0578948 EM
5 -0.62757748D+04 60.6856495 0.0095772 EM
6 -0.62738784D+04 1.8963111 0.0003022 EM
7 -0.62738312D+04 0.0472704 0.0000075 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 19
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.15584923D+05 0.0000000 0.0000000 EM
2 -0.72557998D+04 8329.1229484 0.5344347 EM
3 -0.70569783D+04 198.8214856 0.0274017 EM
4 -0.67924050D+04 264.5732783 0.0374910 EM
5 -0.64404020D+04 352.0030312 0.0518230 EM
6 -0.62843763D+04 156.0257109 0.0242261 EM
7 -0.62741030D+04 10.2732911 0.0016347 EM
8 -0.62738366D+04 0.2664006 0.0000425 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 20
E STEP ITER LOGLIKELIHOOD ABS CHANGE REL CHANGE ALGORITHM
1 -0.19288982D+05 0.0000000 0.0000000 EM
2 -0.69945035D+04 ************ 0.6373835 EM
3 -0.63707415D+04 623.7619790 0.0891789 EM
4 -0.62754283D+04 95.3131980 0.0149611 EM
5 -0.62738505D+04 1.5778152 0.0002514 EM
6 -0.62738302D+04 0.0202994 0.0000032 EM
FINAL STAGE ITERATIONS
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 1
6 -0.62738304D+04 0.0224044 0.0000036 EM
7 -0.62738299D+04 0.0005081 0.0000001 EM
8 -0.62738299D+04 0.0000129 0.0000000 EM
9 -0.62738299D+04 0.0000003 0.0000000 EM
10 -0.62738299D+04 0.0000000 0.0000000 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 20
6 -0.62738302D+04 0.0202994 0.0000032 EM
7 -0.62738299D+04 0.0003257 0.0000001 EM
8 -0.62738299D+04 0.0000062 0.0000000 EM
9 -0.62738299D+04 0.0000001 0.0000000 EM
10 -0.62738299D+04 0.0000000 0.0000000 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 12
5 -0.62738302D+04 0.0193840 0.0000031 EM
6 -0.62738299D+04 0.0003468 0.0000001 EM
7 -0.62738299D+04 0.0000066 0.0000000 EM
8 -0.62738299D+04 0.0000001 0.0000000 EM
9 -0.62738299D+04 0.0000000 0.0000000 EM
TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 15
5 -0.62738301D+04 0.0202503 0.0000032 EM
6 -0.62738299D+04 0.0002506 0.0000000 EM
7 -0.62738299D+04 0.0000036 0.0000000 EM
8 -0.62738299D+04 0.0000001 0.0000000 EM
Beginning Time: 23:13:08
Ending Time: 23:13:08
Elapsed Time: 00:00:00
MUTHEN & MUTHEN
3463 Stoner Ave.
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