Mplus VERSION 7.4
MUTHEN & MUTHEN
06/03/2016   4:19 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;

  MODEL:
      math10 ON math7;

  OUTPUT:
      TECH1 SAMPSTAT STDYX RESIDUAL CINTERVAL;

  Plot:
      TYPE = PLOT3;
      OUTLIERS = LOGLIKELIHOOD COOKS;



*** 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
   3 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                            0

Observed dependent variables

  Continuous
   MATH10

Observed independent variables
   MATH7

Variables with special functions

  ID variable           ID

Estimator                                                       ML
Information matrix                                        OBSERVED
Maximum number of iterations                                  1000
Convergence criterion                                    0.500D-04
Maximum number of steepest descent iterations                   20
Maximum number of iterations for H1                           2000
Convergence criterion for H1                             0.100D-03

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                        3

Loglikelihood

          H0 Value                       -7166.748
          H1 Value                       -7166.748

Information Criteria

          Akaike (AIC)                   14339.496
          Bayesian (BIC)                 14356.327
          Sample-Size Adjusted BIC       14346.796
            (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                           1949.463
          Degrees of Freedom                     1
          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

 MATH10   ON
    MATH7              1.057      0.018     57.301      0.000

 Intercepts
    MATH10             9.171      0.969      9.468      0.000

 Residual Variances
    MATH10            70.912      2.232     31.772      0.000


STANDARDIZED MODEL RESULTS


STDYX Standardization

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

 MATH10   ON
    MATH7              0.787      0.008     92.859      0.000

 Intercepts
    MATH10             0.672      0.078      8.562      0.000

 Residual Variances
    MATH10             0.381      0.013     28.550      0.000


R-SQUARE

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

    MATH10             0.619      0.013     46.430      0.000


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.281E-03
       (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%

 MATH10   ON
    MATH7            1.010       1.021       1.027       1.057       1.087       1.093       1.105

 Intercepts
    MATH10           6.676       7.272       7.578       9.171      10.764      11.069      11.666

 Residual Variances
    MATH10          65.163      66.537      67.240      70.912      74.583      75.286      76.660


CONFIDENCE INTERVALS OF STANDARDIZED MODEL RESULTS


STDYX Standardization

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

 MATH10   ON
    MATH7            0.765       0.770       0.773       0.787       0.801       0.804       0.809

 Intercepts
    MATH10           0.470       0.518       0.543       0.672       0.801       0.826       0.874

 Residual Variances
    MATH10           0.346       0.355       0.359       0.381       0.403       0.407       0.415


RESIDUAL OUTPUT


     ESTIMATED MODEL AND RESIDUALS (OBSERVED - ESTIMATED)


           Model Estimated Means/Intercepts/Thresholds
              MATH10        MATH7
              ________      ________
      1        63.624        51.515


           Residuals for Means/Intercepts/Thresholds
              MATH10        MATH7
              ________      ________
      1         0.000         0.000


           Standardized Residuals (z-scores) for Means/Intercepts/Thresholds
              MATH10        MATH7
              ________      ________
      1         0.583         0.000


           Normalized Residuals for Means/Intercepts/Thresholds
              MATH10        MATH7
              ________      ________
      1         0.000         0.000


           Model Estimated Covariances/Correlations/Residual Correlations
              MATH10        MATH7
              ________      ________
 MATH10       186.231
 MATH7        109.098       103.212


           Residuals for Covariances/Correlations/Residual Correlations
              MATH10        MATH7
              ________      ________
 MATH10         0.000
 MATH7          0.000         0.000


           Standardized Residuals (z-scores) for Covariances/Correlations/Residual Corr
              MATH10        MATH7
              ________      ________
 MATH10         0.005
 MATH7          0.045         0.000


           Normalized Residuals for Covariances/Correlations/Residual Correlations
              MATH10        MATH7
              ________      ________
 MATH10         0.000
 MATH7          0.000         0.000


TECHNICAL 1 OUTPUT


     PARAMETER SPECIFICATION


           NU
              MATH10        MATH7
              ________      ________
      1           0             0


           LAMBDA
              MATH10        MATH7
              ________      ________
 MATH10             0             0
 MATH7              0             0


           THETA
              MATH10        MATH7
              ________      ________
 MATH10             0
 MATH7              0             0


           ALPHA
              MATH10        MATH7
              ________      ________
      1           1             0


           BETA
              MATH10        MATH7
              ________      ________
 MATH10             0             2
 MATH7              0             0


           PSI
              MATH10        MATH7
              ________      ________
 MATH10             3
 MATH7              0             0


     STARTING VALUES


           NU
              MATH10        MATH7
              ________      ________
      1         0.000         0.000


           LAMBDA
              MATH10        MATH7
              ________      ________
 MATH10         1.000         0.000
 MATH7          0.000         1.000


           THETA
              MATH10        MATH7
              ________      ________
 MATH10         0.000
 MATH7          0.000         0.000


           ALPHA
              MATH10        MATH7
              ________      ________
      1        63.624        51.515


           BETA
              MATH10        MATH7
              ________      ________
 MATH10         0.000         0.000
 MATH7          0.000         0.000


           PSI
              MATH10        MATH7
              ________      ________
 MATH10        93.115
 MATH7          0.000       103.212


PLOT INFORMATION

The following plots are available:

  Histograms (sample values, outliers, estimated values, residuals)
  Scatterplots (sample values, outliers, estimated values, residuals)

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\lsay\1-2 p

     Beginning Time:  16:19:30
        Ending Time:  16:19:30
       Elapsed Time:  00:00:00



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