Mplus VERSION 7.3
MUTHEN & MUTHEN
09/22/2014   5:46 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a zero-inflated
  		Poisson regression for a count dependent
  		variable with two covariates
  DATA:		FILE IS ex3.8a.dat;
  VARIABLE:	NAMES ARE u1 x1 x3;
  		COUNT IS u1 (i);
  MODEL:	u1 ON x1 x3;
  		u1#1 ON x1 x3;



INPUT READING TERMINATED NORMALLY



this is an example of a zero-inflated
Poisson regression for a count 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

  Count
   U1

Observed independent variables
   X1          X3


Estimator                                                      MLR
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)
  ex3.8a.dat
Input data format  FREE


COUNT PROPORTION OF ZERO, MINIMUM AND MAXIMUM VALUES

      U1          0.436         0        14



THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                        6

Loglikelihood

          H0 Value                        -758.855
          H0 Scaling Correction Factor      1.0627
            for MLR

Information Criteria

          Akaike (AIC)                    1529.710
          Bayesian (BIC)                  1554.998
          Sample-Size Adjusted BIC        1535.953
            (n* = (n + 2) / 24)



MODEL RESULTS

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

 U1         ON
    X1                 0.548      0.041     13.307      0.000
    X3                 0.309      0.041      7.616      0.000

 U1#1       ON
    X1                 1.629      0.239      6.831      0.000
    X3                 1.055      0.182      5.797      0.000

 Intercepts
    U1#1              -0.950      0.171     -5.562      0.000
    U1                 1.061      0.041     26.106      0.000


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.174E-01
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  17:46:26
        Ending Time:  17:46:26
       Elapsed Time:  00:00:00



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