Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 10:22 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a simple linear
regression for a continuous observed
dependent variable with two covariates
MONTECARLO:
NAMES = y1 x1 x3;
NOBSERVATIONS = 500;
NREPS = 1;
SEED = 53487;
SAVE = ex3.1.dat;
MODEL POPULATION:
[x1-x3@0];
x1-x3@1;
y1 ON x1*1 x3*.5;
y1*1;
[y1*.5];
MODEL:
y1 ON x1*1 x3*.5;
y1*1;
[y1*.5];
INPUT READING TERMINATED NORMALLY
this is an example of a simple linear
regression for a continuous observed
dependent variable with two covariates
SUMMARY OF ANALYSIS
Number of groups 1
Number of observations 500
Number of replications
Requested 1
Completed 1
Value of seed 53487
Number of dependent variables 1
Number of independent variables 2
Number of continuous latent variables 0
Observed dependent variables
Continuous
Y1
Observed independent variables
X1 X3
Estimator ML
Information matrix OBSERVED
Maximum number of iterations 1000
Convergence criterion 0.500D-04
Maximum number of steepest descent iterations 20
SAMPLE STATISTICS FOR THE FIRST REPLICATION
SAMPLE STATISTICS
Means
Y1 X1 X3
________ ________ ________
0.485 0.001 -0.042
Covariances
Y1 X1 X3
________ ________ ________
Y1 2.408
X1 1.078 1.094
X3 0.648 0.028 0.957
Correlations
Y1 X1 X3
________ ________ ________
Y1 1.000
X1 0.665 1.000
X3 0.427 0.028 1.000
MODEL FIT INFORMATION
Number of Free Parameters 4
Loglikelihood
H0 Value
Mean -694.334
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 -694.334 -694.334
0.980 0.000 -694.334 -694.334
0.950 0.000 -694.334 -694.334
0.900 0.000 -694.334 -694.334
0.800 0.000 -694.334 -694.334
0.700 0.000 -694.334 -694.334
0.500 0.000 -694.334 -694.334
0.300 0.000 -694.334 -694.334
0.200 0.000 -694.334 -694.334
0.100 0.000 -694.334 -694.334
0.050 0.000 -694.334 -694.334
0.020 0.000 -694.334 -694.334
0.010 0.000 -694.334 -694.334
H1 Value
Mean -694.334
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 -694.334 -694.334
0.980 0.000 -694.334 -694.334
0.950 0.000 -694.334 -694.334
0.900 0.000 -694.334 -694.334
0.800 0.000 -694.334 -694.334
0.700 0.000 -694.334 -694.334
0.500 0.000 -694.334 -694.334
0.300 0.000 -694.334 -694.334
0.200 0.000 -694.334 -694.334
0.100 0.000 -694.334 -694.334
0.050 0.000 -694.334 -694.334
0.020 0.000 -694.334 -694.334
0.010 0.000 -694.334 -694.334
Information Criteria
Akaike (AIC)
Mean 1396.667
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 1396.667 1396.667
0.980 0.000 1396.667 1396.667
0.950 0.000 1396.667 1396.667
0.900 0.000 1396.667 1396.667
0.800 0.000 1396.667 1396.667
0.700 0.000 1396.667 1396.667
0.500 0.000 1396.667 1396.667
0.300 0.000 1396.667 1396.667
0.200 0.000 1396.667 1396.667
0.100 0.000 1396.667 1396.667
0.050 0.000 1396.667 1396.667
0.020 0.000 1396.667 1396.667
0.010 0.000 1396.667 1396.667
Bayesian (BIC)
Mean 1413.526
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 1413.526 1413.526
0.980 0.000 1413.526 1413.526
0.950 0.000 1413.526 1413.526
0.900 0.000 1413.526 1413.526
0.800 0.000 1413.526 1413.526
0.700 0.000 1413.526 1413.526
0.500 0.000 1413.526 1413.526
0.300 0.000 1413.526 1413.526
0.200 0.000 1413.526 1413.526
0.100 0.000 1413.526 1413.526
0.050 0.000 1413.526 1413.526
0.020 0.000 1413.526 1413.526
0.010 0.000 1413.526 1413.526
Sample-Size Adjusted BIC (n* = (n + 2) / 24)
Mean 1400.830
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 0.000 1400.830 1400.830
0.980 0.000 1400.830 1400.830
0.950 0.000 1400.830 1400.830
0.900 0.000 1400.830 1400.830
0.800 0.000 1400.830 1400.830
0.700 0.000 1400.830 1400.830
0.500 0.000 1400.830 1400.830
0.300 0.000 1400.830 1400.830
0.200 0.000 1400.830 1400.830
0.100 0.000 1400.830 1400.830
0.050 0.000 1400.830 1400.830
0.020 0.000 1400.830 1400.830
0.010 0.000 1400.830 1400.830
Chi-Square Test of Model Fit
Degrees of freedom 0
Mean 0.000
Std Dev 0.000
Number of successful computations 1
Proportions Percentiles
Expected Observed Expected Observed
0.990 1.000 0.000 0.000
0.980 1.000 0.000 0.000
0.950 1.000 0.000 0.000
0.900 1.000 0.000 0.000
0.800 1.000 0.000 0.000
0.700 1.000 0.000 0.000
0.500 1.000 0.000 0.000
0.300 1.000 0.000 0.000
0.200 1.000 0.000 0.000
0.100 1.000 0.000 0.000
0.050 1.000 0.000 0.000
0.020 1.000 0.000 0.000
0.010 1.000 0.000 0.000
RMSEA (Root Mean Square Error Of Approximation)
Mean 0.000
Std Dev 0.000
Number of successful computations 1
Cumulative Distribution Function
Value Function Value
0.990 1.000
0.980 1.000
0.950 1.000
0.900 1.000
0.800 1.000
0.700 1.000
0.500 1.000
0.300 1.000
0.200 1.000
0.100 1.000
0.050 1.000
0.020 1.000
0.010 1.000
CFI/TLI
CFI
Mean 1.000
Std Dev 0.000
Number of successful computations 1
Cumulative Distribution Function
Value Function Value
0.990 0.000
0.980 0.000
0.950 0.000
0.900 0.000
0.800 0.000
0.700 0.000
0.500 0.000
0.300 0.000
0.200 0.000
0.100 0.000
0.050 0.000
0.020 0.000
0.010 0.000
TLI
Mean 1.000
Std Dev 0.000
Number of successful computations 1
Cumulative Distribution Function
Value Function Value
0.990 0.000
0.980 0.000
0.950 0.000
0.900 0.000
0.800 0.000
0.700 0.000
0.500 0.000
0.300 0.000
0.200 0.000
0.100 0.000
0.050 0.000
0.020 0.000
0.010 0.000
SRMR (Standardized Root Mean Square Residual)
Mean 0.000
Std Dev 0.000
Number of successful computations 1
Cumulative Distribution Function
Value Function Value
0.990 1.000
0.980 1.000
0.950 1.000
0.900 1.000
0.800 1.000
0.700 1.000
0.500 1.000
0.300 1.000
0.200 1.000
0.100 1.000
0.050 1.000
0.020 1.000
0.010 1.000
MODEL RESULTS
ESTIMATES S. E. M. S. E. 95% % Sig
Population Average Std. Dev. Average Cover Coeff
Y1 ON
X1 1.000 0.9695 0.0000 0.0415 0.0009 1.000 1.000
X3 0.500 0.6490 0.0000 0.0444 0.0222 0.000 1.000
Intercepts
Y1 0.500 0.5110 0.0000 0.0434 0.0001 1.000 1.000
Residual Variances
Y1 1.000 0.9413 0.0000 0.0595 0.0034 1.000 1.000
QUALITY OF NUMERICAL RESULTS
Average Condition Number for the Information Matrix 0.483E+00
(ratio of smallest to largest eigenvalue)
TECHNICAL OUTPUT
PARAMETER SPECIFICATION
NU
Y1 X1 X3
________ ________ ________
0 0 0
LAMBDA
Y1 X1 X3
________ ________ ________
Y1 0 0 0
X1 0 0 0
X3 0 0 0
THETA
Y1 X1 X3
________ ________ ________
Y1 0
X1 0 0
X3 0 0 0
ALPHA
Y1 X1 X3
________ ________ ________
1 0 0
BETA
Y1 X1 X3
________ ________ ________
Y1 0 2 3
X1 0 0 0
X3 0 0 0
PSI
Y1 X1 X3
________ ________ ________
Y1 4
X1 0 0
X3 0 0 0
STARTING VALUES
NU
Y1 X1 X3
________ ________ ________
0.000 0.000 0.000
LAMBDA
Y1 X1 X3
________ ________ ________
Y1 1.000 0.000 0.000
X1 0.000 1.000 0.000
X3 0.000 0.000 1.000
THETA
Y1 X1 X3
________ ________ ________
Y1 0.000
X1 0.000 0.000
X3 0.000 0.000 0.000
ALPHA
Y1 X1 X3
________ ________ ________
0.500 0.001 -0.042
BETA
Y1 X1 X3
________ ________ ________
Y1 0.000 1.000 0.500
X1 0.000 0.000 0.000
X3 0.000 0.000 0.000
PSI
Y1 X1 X3
________ ________ ________
Y1 1.000
X1 0.000 1.094
X3 0.000 0.028 0.957
POPULATION VALUES
NU
Y1 X1 X3
________ ________ ________
0.000 0.000 0.000
LAMBDA
Y1 X1 X3
________ ________ ________
Y1 1.000 0.000 0.000
X1 0.000 1.000 0.000
X3 0.000 0.000 1.000
THETA
Y1 X1 X3
________ ________ ________
Y1 0.000
X1 0.000 0.000
X3 0.000 0.000 0.000
ALPHA
Y1 X1 X3
________ ________ ________
0.500 0.000 0.000
BETA
Y1 X1 X3
________ ________ ________
Y1 0.000 1.000 0.500
X1 0.000 0.000 0.000
X3 0.000 0.000 0.000
PSI
Y1 X1 X3
________ ________ ________
Y1 1.000
X1 0.000 1.000
X3 0.000 0.000 1.000
SAVEDATA INFORMATION
Order of variables
Y1
X1
X3
Save file
ex3.1.dat
Save file format Free
Save file record length 10000
Beginning Time: 22:22:32
Ending Time: 22:22:32
Elapsed Time: 00:00:00
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