Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022 11:09 PM
INPUT INSTRUCTIONS
TITLE: this is an example of a simple linear
regression for a continuous observed
dependent variable with two covariates
DATA: FILE IS ex3.1.dat;
VARIABLE: NAMES ARE y1 x1 x3;
MODEL: y1 ON x1 x3;
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 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
Input data file(s)
ex3.1.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 0.485 -0.012 -4.116 0.20% -0.768 0.070 0.429
500.000 2.408 -0.136 5.111 0.20% 0.777 1.894
X1 0.001 -0.133 -3.145 0.20% -0.922 -0.235 0.023
500.000 1.094 -0.162 2.920 0.20% 0.304 0.876
X3 -0.042 -0.057 -3.139 0.20% -0.921 -0.353 -0.040
500.000 0.957 -0.357 2.875 0.20% 0.274 0.859
THE MODEL ESTIMATION TERMINATED NORMALLY
MODEL FIT INFORMATION
Number of Free Parameters 4
Loglikelihood
H0 Value -694.334
H1 Value -694.334
Information Criteria
Akaike (AIC) 1396.667
Bayesian (BIC) 1413.526
Sample-Size Adjusted BIC 1400.830
(n* = (n + 2) / 24)
Chi-Square Test of Model Fit
Value 0.000
Degrees of Freedom 0
P-Value 0.0000
RMSEA (Root Mean Square Error Of Approximation)
Estimate 0.000
90 Percent C.I. 0.000 0.000
Probability RMSEA <= .05 0.000
CFI/TLI
CFI 1.000
TLI 1.000
Chi-Square Test of Model Fit for the Baseline Model
Value 469.585
Degrees of Freedom 2
P-Value 0.0000
SRMR (Standardized Root Mean Square Residual)
Value 0.000
MODEL RESULTS
Two-Tailed
Estimate S.E. Est./S.E. P-Value
Y1 ON
X1 0.969 0.042 23.356 0.000
X3 0.649 0.044 14.626 0.000
Intercepts
Y1 0.511 0.043 11.765 0.000
Residual Variances
Y1 0.941 0.060 15.811 0.000
QUALITY OF NUMERICAL RESULTS
Condition Number for the Information Matrix 0.483E+00
(ratio of smallest to largest eigenvalue)
Beginning Time: 23:09:14
Ending Time: 23:09:14
Elapsed Time: 00:00:00
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