Mplus VERSION 8.7 (Mac) MUTHEN & MUTHEN 10/21/2021 10:45 PM INPUT INSTRUCTIONS TITLE: this is an example of a multinomial logistic regression for an unordered categorical (nominal) dependent variable with two covariates DATA: FILE IS ex3.6.dat; VARIABLE: NAMES ARE u1 x1 x3; NOMINAL IS u1; MODEL: u1 ON x1 x3; INPUT READING TERMINATED NORMALLY this is an example of a multinomial logistic regression for an unordered categorical (nominal) 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 Unordered categorical (nominal) 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) ex3.6.dat Input data format FREE UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES U1 Category 1 0.242 121.000 Category 2 0.368 184.000 Category 3 0.390 195.000 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 6 Loglikelihood H0 Value -433.426 H0 Scaling Correction Factor 1.0174 for MLR Information Criteria Akaike (AIC) 878.853 Bayesian (BIC) 904.140 Sample-Size Adjusted BIC 885.096 (n* = (n + 2) / 24) MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value U1#1 ON X1 0.769 0.165 4.669 0.000 X3 2.259 0.203 11.147 0.000 U1#2 ON X1 0.280 0.114 2.444 0.015 X3 0.885 0.143 6.200 0.000 Intercepts U1#1 -0.749 0.158 -4.728 0.000 U1#2 0.262 0.120 2.192 0.028 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.849E-01 (ratio of smallest to largest eigenvalue) LOGISTIC REGRESSION ODDS RATIO RESULTS 95% C.I. Estimate S.E. Lower 2.5% Upper 2.5% U1#1 ON X1 2.157 0.355 1.562 2.978 X3 9.578 1.941 6.438 14.249 U1#2 ON X1 1.323 0.151 1.057 1.656 X3 2.423 0.346 1.832 3.206 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