Mplus VERSION 8.7 (Mac) MUTHEN & MUTHEN 10/21/2021 10:45 PM INPUT INSTRUCTIONS TITLE: this is an example of a Poisson regression for a count dependent variable with two covariates DATA: FILE IS ex3.7.dat; VARIABLE: NAMES ARE u1 x1 x3; COUNT IS u1; MODEL: u1 ON x1 x3; INPUT READING TERMINATED NORMALLY this is an example of a 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) ex3.7.dat Input data format FREE COUNT PROPORTION OF ZERO, MINIMUM AND MAXIMUM VALUES U1 0.112 0 27 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 X1 0.000 -0.035 -3.139 0.20% -0.842 -0.239 -0.016 500.000 1.041 0.091 3.252 0.20% 0.254 0.887 X3 -0.067 -0.060 -3.145 0.20% -0.870 -0.304 -0.034 500.000 0.960 0.073 2.857 0.20% 0.205 0.741 THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 3 Loglikelihood H0 Value -966.884 H0 Scaling Correction Factor 1.2053 for MLR Information Criteria Akaike (AIC) 1939.768 Bayesian (BIC) 1952.412 Sample-Size Adjusted BIC 1942.890 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value U1 ON X1 0.533 0.027 19.795 0.000 X3 0.249 0.026 9.780 0.000 Intercepts U1 1.026 0.030 34.033 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.235E+00 (ratio of smallest to largest eigenvalue) Beginning Time: 22:45:56 Ending Time: 22:45:56 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) 1998-2021 Muthen & Muthen