Mplus VERSION 7.4
MUTHEN & MUTHEN
06/06/2016   5:37 PM

INPUT INSTRUCTIONS

  TITLE:
      Multinomial regression of antisocial behavior in the NLSY

  DATA:
  	FILE = ASBcprobs5.dat;

  VARIABLE:
  	NAMES = property fight shoplift lt50 gt50 force threat injure pot drug
  	soldpot solddrug con auto bldg goods gambling
  	male black age94 dropout cprob1-cprob5 u;

      ! u is type of antisocial behavior:
      ! all (1), property (2), drug (3), person (4), normative (5)
      ! age94 is scored 0-7 for ages 16-23

      USEVARiables =  male-dropout u;

      nominal = u;

  Analysis:
      estimator = ml;

  model:
      u on male-dropout;

  plot:
      type = plot3;



INPUT READING TERMINATED NORMALLY




Multinomial regression of antisocial behavior in the NLSY

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        7326

Number of dependent variables                                    1
Number of independent variables                                  4
Number of continuous latent variables                            0

Observed dependent variables

  Unordered categorical (nominal)
   U

Observed independent variables
   MALE        BLACK       AGE94       DROPOUT


Estimator                                                       ML
Information matrix                                        OBSERVED
Optimization Specifications for the Quasi-Newton Algorithm for
Continuous Outcomes
  Maximum number of iterations                                 100
  Convergence criterion                                  0.100D-05
Optimization Specifications for the EM Algorithm
  Maximum number of iterations                                 500
  Convergence criteria
    Loglikelihood change                                 0.100D-02
    Relative loglikelihood change                        0.100D-05
    Derivative                                           0.100D-02
Optimization Specifications for the M step of the EM Algorithm for
Categorical Latent variables
  Number of M step iterations                                    1
  M step convergence criterion                           0.100D-02
  Basis for M step termination                           ITERATION
Optimization Specifications for the M step of the EM Algorithm for
Censored, Binary or Ordered Categorical (Ordinal), Unordered
Categorical (Nominal) and Count Outcomes
  Number of M step iterations                                    1
  M step convergence criterion                           0.100D-02
  Basis for M step termination                           ITERATION
  Maximum value for logit thresholds                            15
  Minimum value for logit thresholds                           -15
  Minimum expected cell size for chi-square              0.100D-01
Optimization algorithm                                         EMA
Integration Specifications
  Type                                                    STANDARD
  Number of integration points                                  15
  Dimensions of numerical integration                            0
  Adaptive quadrature                                           ON
Cholesky                                                       OFF

Input data file(s)
  ASBcprobs5.dat
Input data format  FREE


UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    U
      Category 1    0.019          136.000
      Category 2    0.112          823.000
      Category 3    0.162         1190.000
      Category 4    0.259         1895.000
      Category 5    0.448         3282.000



THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                       20

Loglikelihood

          H0 Value                       -9191.205

Information Criteria

          Akaike (AIC)                   18422.411
          Bayesian (BIC)                 18560.394
          Sample-Size Adjusted BIC       18496.839
            (n* = (n + 2) / 24)



MODEL RESULTS

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

 U#1        ON
    MALE               2.924      0.317      9.228      0.000
    BLACK             -0.148      0.201     -0.738      0.460
    AGE94             -0.145      0.042     -3.423      0.001
    DROPOUT            0.882      0.208      4.250      0.000

 U#2        ON
    MALE               1.600      0.089     18.054      0.000
    BLACK             -0.114      0.090     -1.268      0.205
    AGE94             -0.142      0.019     -7.435      0.000
    DROPOUT            0.426      0.110      3.868      0.000

 U#3        ON
    MALE               0.159      0.069      2.289      0.022
    BLACK             -0.670      0.084     -7.949      0.000
    AGE94              0.080      0.016      5.164      0.000
    DROPOUT           -0.282      0.115     -2.452      0.014

 U#4        ON
    MALE               0.848      0.060     14.243      0.000
    BLACK              0.402      0.062      6.478      0.000
    AGE94             -0.133      0.014     -9.582      0.000
    DROPOUT            0.042      0.089      0.474      0.635

 Intercepts
    U#1               -4.930      0.328    -15.039      0.000
    U#2               -1.926      0.093    -20.712      0.000
    U#3               -1.154      0.072    -16.085      0.000
    U#4               -0.722      0.061    -11.771      0.000


LOGISTIC REGRESSION ODDS RATIO RESULTS

 U#1        ON
    MALE              18.616
    BLACK              0.862
    AGE94              0.865
    DROPOUT            2.416

 U#2        ON
    MALE               4.952
    BLACK              0.892
    AGE94              0.868
    DROPOUT            1.531

 U#3        ON
    MALE               1.172
    BLACK              0.511
    AGE94              1.084
    DROPOUT            0.754

 U#4        ON
    MALE               2.335
    BLACK              1.494
    AGE94              0.875
    DROPOUT            1.043


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.232E-03
       (ratio of smallest to largest eigenvalue)


PLOT INFORMATION

The following plots are available:

  Histograms (sample values)
  Scatterplots (sample values)
  Sample proportions, estimated and conditional estimated probabilities

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\gryphon\desktop\chapter5\ex5.22.dgm

     Beginning Time:  17:37:33
        Ending Time:  17:37:33
       Elapsed Time:  00:00:00



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