Mplus VERSION 7.4
MUTHEN & MUTHEN
11/09/2015   5:40 PM

INPUT INSTRUCTIONS


  TITLE:  Regressing math10 on math7

  DATA:
      FILE = dropout.dat;
      FORMAT = 11f8 6f8.2 1f8 2f8.2 10f2;

  VARIABLE:
      NAMES ARE id school gender mothed fathed fathsei ethnic expect
              pacpush pmpush homeres
               math7 math8 math9 math10 math11 math12 problem esteem mathatt
               clocatn dlocatn elocatn flocatn glocatn hlocatn ilocatn jlocatn
              klocatn llocatn;
      MISSING = mothed (8) fathed (8)  fathsei (996 998)
                ethnic (8) homeres (98) math7-math12 (996 998);
      IDVARIABLE = id;
      USEVAR = math7 math10;

  Analysis:
      type = random;

  MODEL:
      s | math10 ON math7;
      s with math10 (cov);
      math10 (resvary);
      s (vbeta);

  OUTPUT:
      TECH1 SAMPSTAT STDYX RESIDUAL CINTERVAL;

  Plot:
      TYPE = PLOT3;

  Model constraint:
      plot (vygivenx);
      loop(x,25,90,1);
      vygivenx = vbeta*x*x + 2*cov*x + resvary;





*** WARNING in OUTPUT command
  STANDARDIZED (STD, STDY, STDYX) options for TYPE=RANDOM require ALGORITHM=INTEGRATION.
  Request for STANDARDIZED (STD, STDY, STDYX) is ignored.
*** WARNING in OUTPUT command
  RESIDUAL option for TYPE=RANDOM requires ALGORITHM=INTEGRATION.
  Request for RESIDUAL is ignored.
*** WARNING
  Data set contains cases with missing on all variables.
  These cases were not included in the analysis.
  Number of cases with missing on all variables:  30
*** WARNING
  Data set contains cases with missing on x-variables.
  These cases were not included in the analysis.
  Number of cases with missing on x-variables:  21
*** WARNING
  Data set contains cases with missing on all variables except
  x-variables.  These cases were not included in the analysis.
  Number of cases with missing on all variables except x-variables:  1046
   5 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS



Regressing math10 on math7

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        2019

Number of dependent variables                                    1
Number of independent variables                                  1
Number of continuous latent variables                            1

Observed dependent variables

  Continuous
   MATH10

Observed independent variables
   MATH7

Continuous latent variables
   S

Variables with special functions

  ID variable           ID

Estimator                                                      MLR
Information matrix                                        OBSERVED
Maximum number of iterations                                   100
Convergence criterion                                    0.100D-05
Maximum number of EM iterations                                500
Convergence criteria for the EM algorithm
  Loglikelihood change                                   0.100D-02
  Relative loglikelihood change                          0.100D-05
  Derivative                                             0.100D-03
Minimum variance                                         0.100D-03
Maximum number of steepest descent iterations                   20
Maximum number of iterations for H1                           2000
Convergence criterion for H1                             0.100D-03
Optimization algorithm                                         EMA

Input data file(s)
  dropout.dat
Input data format
  (11F8 6F8.2 1F8 2F8.2 10F2)


SUMMARY OF DATA

     Number of missing data patterns             1


COVARIANCE COVERAGE OF DATA

Minimum covariance coverage value   0.100


     PROPORTION OF DATA PRESENT


           Covariance Coverage
              MATH10        MATH7
              ________      ________
 MATH10         1.000
 MATH7          1.000         1.000


SAMPLE STATISTICS


     ESTIMATED SAMPLE STATISTICS


           Means
              MATH10        MATH7
              ________      ________
 1             63.624        51.515


           Covariances
              MATH10        MATH7
              ________      ________
 MATH10       186.231
 MATH7        109.098       103.212


           Correlations
              MATH10        MATH7
              ________      ________
 MATH10         1.000
 MATH7          0.787         1.000


     MAXIMUM LOG-LIKELIHOOD VALUE FOR THE UNRESTRICTED (H1) MODEL IS -14712.416


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

     MATH10               63.624      -0.321      29.600    0.05%      51.490     61.860     65.340
            2019.000     186.231      -0.459      95.170    0.25%      68.400     75.290
     MATH7                51.515       0.050      27.560    0.05%      42.080     48.670     51.810
            2019.000     103.212      -0.621      85.020    0.05%      54.390     60.650


THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                        5

Loglikelihood

          H0 Value                       -7078.820
          H0 Scaling Correction Factor      1.1700
            for MLR

Information Criteria

          Akaike (AIC)                   14167.639
          Bayesian (BIC)                 14195.691
          Sample-Size Adjusted BIC       14179.806
            (n* = (n + 2) / 24)



MODEL RESULTS

                                                    Two-Tailed
                    Estimate       S.E.  Est./S.E.    P-Value

 S        WITH
    MATH10            -4.413      0.841     -5.247      0.000

 Means
    S                  1.053      0.017     61.778      0.000

 Intercepts
    MATH10             9.410      0.972      9.685      0.000

 Variances
    S                  0.056      0.014      3.963      0.000

 Residual Variances
    MATH10           372.259     49.361      7.542      0.000


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.353E-09
       (ratio of smallest to largest eigenvalue)


CONFIDENCE INTERVALS OF MODEL RESULTS

                  Lower .5%  Lower 2.5%    Lower 5%    Estimate    Upper 5%  Upper 2.5%   Upper .5%

 S        WITH
    MATH10          -6.580      -6.062      -5.797      -4.413      -3.030      -2.765      -2.247

 Means
    S                1.009       1.019       1.025       1.053       1.081       1.086       1.097

 Intercepts
    MATH10           6.907       7.505       7.811       9.410      11.008      11.314      11.912

 Variances
    S                0.020       0.028       0.033       0.056       0.079       0.084       0.092

 Residual Variances
    MATH10         245.115     275.511     291.060     372.259     453.458     469.007     499.404


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION


           NU
              MATH10        MATH7
              ________      ________
 1                  0             0


           LAMBDA
              S             MATH10        MATH7
              ________      ________      ________
 MATH10             0             0             0
 MATH7              0             0             0


           THETA
              MATH10        MATH7
              ________      ________
 MATH10             0
 MATH7              0             0


           ALPHA
              S             MATH10        MATH7
              ________      ________      ________
 1                  1             2             0


           BETA
              S             MATH10        MATH7
              ________      ________      ________
 S                  0             0             0
 MATH10             0             0             0
 MATH7              0             0             0


           PSI
              S             MATH10        MATH7
              ________      ________      ________
 S                  3
 MATH10             4             5
 MATH7              0             0             0


     PARAMETER SPECIFICATION FOR THE ADDITIONAL PARAMETERS


           NEW/ADDITIONAL PARAMETERS
              VYGIVENX      X
              ________      ________
 1                  6             7


     STARTING VALUES


           NU
              MATH10        MATH7
              ________      ________
 1              0.000         0.000


           LAMBDA
              S             MATH10        MATH7
              ________      ________      ________
 MATH10         0.000         1.000         0.000
 MATH7          0.000         0.000         1.000


           THETA
              MATH10        MATH7
              ________      ________
 MATH10         0.000
 MATH7          0.000         0.000


           ALPHA
              S             MATH10        MATH7
              ________      ________      ________
 1              0.000        63.624         0.000


           BETA
              S             MATH10        MATH7
              ________      ________      ________
 S              0.000         0.000         0.000
 MATH10         0.000         0.000         0.000
 MATH7          0.000         0.000         0.000


           PSI
              S             MATH10        MATH7
              ________      ________      ________
 S              1.000
 MATH10         0.000        93.115
 MATH7          0.000         0.000        51.606


     STARTING VALUES FOR THE ADDITIONAL PARAMETERS


           NEW/ADDITIONAL PARAMETERS
              VYGIVENX      X
              ________      ________
 1              0.500         0.000


SAMPLE STATISTICS FOR ESTIMATED FACTOR SCORES


     SAMPLE STATISTICS


           Means
              S             S_SE
              ________      ________
 1              1.053         0.147


           Covariances
              S             S_SE
              ________      ________
 S              0.033
 S_SE           0.000         0.001


           Correlations
              S             S_SE
              ________      ________
 S              1.000
 S_SE          -0.012         1.000


PLOT INFORMATION

The following plots are available:

  Histograms (sample values, estimated factor scores)
  Scatterplots (sample values, estimated factor scores)
  Loop plots
  Latent variable distribution plots

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:\users\bengt 2013\documents\bengt\mplus runs\a book - topic 1 mplus runs\regression\random coe

     Beginning Time:  17:40:45
        Ending Time:  17:40:51
       Elapsed Time:  00:00:06



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) 1998-2015 Muthen & Muthen

Back to examples