Mplus VERSION 8
MUTHEN & MUTHEN
04/10/2017   4:39 AM

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:  04:39:37
        Ending Time:  04:39:37
       Elapsed Time:  00:00:00



MUTHEN & MUTHEN
3463 Stoner Ave.
Los Angeles, CA  90066

Tel: (310) 391-9971
Fax: (310) 391-8971
Web: www.StatModel.com
Support: Support@StatModel.com

Copyright (c) 1998-2017 Muthen & Muthen
