Mplus VERSION 8.6
MUTHEN & MUTHEN
07/20/2021 6:00 PM
OUTPUT SECTIONS
INPUT INSTRUCTIONS
TITLE: 7.3 LGM Modèle linéaire (ajout PLOT & OUTPUT)
DATA:
FILE = Cortisol.dat ;
LISTWISE = ON ;
VARIABLE:
NAMES =
SID C1 C2 C3 C4
SEXE TTT CREVEIL
T1 T2 T3 T4
TC1 TC2 TC3 TC4
FCT ;
USEVARIABLES = C1 C2 C3 C4 ;
ANALYSIS:
ESTIMATOR = MLR ;
MODEL:
i s | C1@0 C2@1 C3@2 C4@3 ;
OUTPUT:
SAMPSTAT STDYX TECH4 ;
PLOT:
TYPE = PLOT3 ;
SERIES = C1-C4 (s) ;
INPUT READING TERMINATED NORMALLY
7.3 LGM Modèle linéaire (ajout PLOT & OUTPUT)
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 101
Number of dependent variables 4
Number of independent variables 0
Number of continuous latent variables 2
Observed dependent variables
Continuous
C1 C2 C3 C4
Continuous latent variables
I S
Estimator MLR
Information matrix OBSERVED
Maximum number of iterations 1000
Convergence criterion 0.500D-04
Maximum number of steepest descent iterations 20
Input data file(s)
Cortisol.dat
Input data format FREE
SAMPLE STATISTICS
SAMPLE STATISTICS
Means
C1 C2 C3 C4
________ ________ ________ ________
10.412 10.189 6.393 3.706
Covariances
C1 C2 C3 C4
________ ________ ________ ________
C1 45.592
C2 22.137 36.375
C3 0.437 3.455 22.701
C4 -1.599 0.641 3.507 5.026
Correlations
C1 C2 C3 C4
________ ________ ________ ________
C1 1.000
C2 0.544 1.000
C3 0.014 0.120 1.000
C4 -0.106 0.047 0.328 1.000
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
C1 10.412 1.383 1.205 0.99% 4.540 7.500 9.168
101.000 45.592 2.806 36.490 0.99% 10.490 15.275
C2 10.189 1.502 1.380 0.99% 5.190 6.885 8.637
101.000 36.375 2.786 33.265 0.99% 10.520 14.420
C3 6.393 2.088 1.825 0.99% 3.225 4.150 4.635
101.000 22.701 4.553 27.110 0.99% 5.155 8.620
C4 3.706 2.704 1.370 0.99% 2.170 2.880 3.123
101.000 5.026 9.698 15.955 0.99% 3.335 4.630
THIS ANALYSIS MAY HAVE MULTIPLE SOLUTIONS. EXPLORE THIS USING RANDOM STARTS,
FOR EXAMPLE, STARTS = 20. USE A LARGE ENOUGH NUMBER OF STARTS SO THAT THE
BEST FIT FUNCTION VALUE IS REPLICATED SEVERAL TIMES.
THE MODEL ESTIMATION TERMINATED NORMALLY
WARNING: THE RESIDUAL COVARIANCE MATRIX (THETA) IS NOT POSITIVE DEFINITE.
THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL VARIANCE FOR AN OBSERVED
VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE BETWEEN TWO OBSERVED
VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO OBSERVED VARIABLES.
CHECK THE RESULTS SECTION FOR MORE INFORMATION.
PROBLEM INVOLVING VARIABLE C4.
MODEL FIT INFORMATION
Number of Free Parameters 9
Loglikelihood
H0 Value -1172.392
H0 Scaling Correction Factor 2.1973
for MLR
H1 Value -1161.416
H1 Scaling Correction Factor 1.7889
for MLR
Information Criteria
Akaike (AIC) 2362.783
Bayesian (BIC) 2386.319
Sample-Size Adjusted BIC 2357.893
(n* = (n + 2) / 24)
Chi-Square Test of Model Fit
Value 20.828*
Degrees of Freedom 5
P-Value 0.0009
Scaling Correction Factor 1.0539
for MLR
* The chi-square value for MLM, MLMV, MLR, ULSMV, WLSM and WLSMV cannot be used
for chi-square difference testing in the regular way. MLM, MLR and WLSM
chi-square difference testing is described on the Mplus website. MLMV, WLSMV,
and ULSMV difference testing is done using the DIFFTEST option.
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.177
90 Percent C.I. 0.103 0.259
Probability RMSEA <= .05 0.004
CFI/TLI
CFI 0.571
TLI 0.485
Chi-Square Test of Model Fit for the Baseline Model
Value 42.868
Degrees of Freedom 6
P-Value 0.0000
SRMR (Standardized Root Mean Square Residual)
Value 0.105
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
I |
C1 1.000 0.000 999.000 999.000
C2 1.000 0.000 999.000 999.000
C3 1.000 0.000 999.000 999.000
C4 1.000 0.000 999.000 999.000
S |
C1 0.000 0.000 999.000 999.000
C2 1.000 0.000 999.000 999.000
C3 2.000 0.000 999.000 999.000
C4 3.000 0.000 999.000 999.000
S WITH
I -9.029 3.039 -2.971 0.003
Means
I 11.286 0.662 17.047 0.000
S -2.533 0.239 -10.585 0.000
Intercepts
C1 0.000 0.000 999.000 999.000
C2 0.000 0.000 999.000 999.000
C3 0.000 0.000 999.000 999.000
C4 0.000 0.000 999.000 999.000
Variances
I 25.574 9.128 2.802 0.005
S 3.811 1.081 3.527 0.000
Residual Variances
C1 20.622 7.341 2.809 0.005
C2 24.159 6.530 3.699 0.000
C3 20.475 5.931 3.452 0.001
C4 -0.685 1.622 -0.422 0.673
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.161E-03
(ratio of smallest to largest eigenvalue)
STANDARDIZED MODEL RESULTS
STDYX Standardization
Two-Tailed
Estimate S.E. Est./S.E. P-Value
I |
C1 0.744 0.097 7.665 0.000
C2 0.849 0.138 6.173 0.000
C3 1.008 0.176 5.735 0.000
C4 2.257 0.573 3.939 0.000
S |
C1 0.000 0.000 999.000 999.000
C2 0.328 0.046 7.052 0.000
C3 0.778 0.112 6.967 0.000
C4 2.614 0.496 5.276 0.000
S WITH
I -0.914 0.041 -22.243 0.000
Means
I 2.232 0.368 6.063 0.000
S -1.297 0.191 -6.779 0.000
Intercepts
C1 0.000 0.000 999.000 999.000
C2 0.000 0.000 999.000 999.000
C3 0.000 0.000 999.000 999.000
C4 0.000 0.000 999.000 999.000
Variances
I 1.000 0.000 999.000 999.000
S 1.000 0.000 999.000 999.000
Residual Variances
C1 0.446 0.144 3.091 0.002
C2 0.681 0.103 6.625 0.000
C3 0.813 0.059 13.868 0.000
C4 -0.136 999.000 999.000 999.000
R-SQUARE
Observed Two-Tailed
Variable Estimate S.E. Est./S.E. P-Value
C1 0.554 0.144 3.833 0.000
C2 0.319 0.103 3.107 0.002
C3 0.187 0.059 3.186 0.001
C4 Undefined 0.11364E+01
TECHNICAL 4 OUTPUT
ESTIMATES DERIVED FROM THE MODEL
ESTIMATED MEANS FOR THE LATENT VARIABLES
I S
________ ________
11.286 -2.533
S.E. FOR ESTIMATED MEANS FOR THE LATENT VARIABLES
I S
________ ________
0.662 0.239
EST./S.E. FOR ESTIMATED MEANS FOR THE LATENT VARIABLES
I S
________ ________
17.047 -10.585
TWO-TAILED P-VALUE FOR ESTIMATED MEANS FOR THE LATENT VARIABLES
I S
________ ________
0.000 0.000
ESTIMATED COVARIANCE MATRIX FOR THE LATENT VARIABLES
I S
________ ________
I 25.574
S -9.029 3.811
S.E. FOR ESTIMATED COVARIANCE MATRIX FOR THE LATENT VARIABLES
I S
________ ________
I 9.128
S 3.039 1.081
EST./S.E. FOR ESTIMATED COVARIANCE MATRIX FOR THE LATENT VARIABLES
I S
________ ________
I 2.802
S -2.971 3.527
TWO-TAILED P-VALUE FOR ESTIMATED COVARIANCE MATRIX FOR THE LATENT VARIABLES
I S
________ ________
I 0.005
S 0.003 0.000
ESTIMATED CORRELATION MATRIX FOR THE LATENT VARIABLES
I S
________ ________
I 1.000
S -0.914 1.000
S.E. FOR ESTIMATED CORRELATION MATRIX FOR THE LATENT VARIABLES
I S
________ ________
I 0.000
S 0.041 0.000
EST./S.E. FOR ESTIMATED CORRELATION MATRIX FOR THE LATENT VARIABLES
I S
________ ________
I 999.000
S -22.243 999.000
TWO-TAILED P-VALUE FOR ESTIMATED CORRELATION MATRIX FOR THE LATENT VARIABLES
I S
________ ________
I 0.000
S 0.000 0.000
SAMPLE STATISTICS FOR ESTIMATED FACTOR SCORES
SAMPLE STATISTICS
Means
I I_SE S S_SE
________ ________ ________ ________
11.287 2.978 -2.533 0.922
Covariances
I I_SE S S_SE
________ ________ ________ ________
I 16.707
I_SE 0.000 0.000
S -6.145 0.000 2.962
S_SE 0.000 0.000 0.000 0.000
Correlations
I I_SE S S_SE
________ ________ ________ ________
I 1.000
I_SE 999.000 1.000
S -0.874 999.000 1.000
S_SE 999.000 999.000 999.000 1.000
PLOT INFORMATION
The following plots are available:
Histograms (sample values, estimated factor scores, estimated values, residuals)
Scatterplots (sample values, estimated factor scores, estimated values, residuals)
Sample means
Estimated means
Sample and estimated means
Latent variable distribution plots
Observed individual values
Estimated individual values
DIAGRAM INFORMATION
Use View Diagram under the Diagram menu in the Mplus Editor to view the diagram.
If running Mplus from the Mplus Diagrammer, the diagram opens automatically.
Diagram output
c:\project\mpluslivre\stx\chapitres\chapitre_07\script7.3.dgm
Beginning Time: 18:00:11
Ending Time: 18:00:11
Elapsed Time: 00:00:00
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