Mplus VERSION 7.11 MUTHEN & MUTHEN 01/20/2014 9:34 AM INPUT INSTRUCTIONS TITLE: Kapitel 6, Abschnitt 6.5.3, Mardias Tests auf multivariate Normalverteilung !Einlesen der Daten DATA: FILE IS daten-kapitel-6.dat; VARIABLE: !Variablen im Datensatz NAMES ARE gender item1-item6; !Variablen in der Analyse USEVARIABLES ARE item1-item6; ! Mardias Tests kann nur anhand einer Mischverteilungsanalyse ! durchgeführt werden. Da die Tests für die beobachtbaren Variablen ! in der Gesamtstichprobe durchgeführt werden soll ! muss eine Klasse vorgegeben werden classes = c(1); ANALYSIS: ! "Type is mixture" fordert Mischverteilungsanalyse an TYPE IS mixture; ESTIMATOR IS ML; ITERATIONS = 1000; CONVERGENCE = 0.00005; Model: ! Gesamtmodell wird angefordert, da nur eine Klasse spezifiziert ! wird, entspricht dies dem Modell in der Gesamtpopulation %overall% !Definition des Modells, erste Ladung durch Voreinstellung auf 1 fixiert; !weitere Ladungen auf 1 fixiert mit @1 eta by item1 item2@1 item3@1 item4@1 item5@1 item6@1; ! Mardias Tests werden angefordert OUTPUT: TECH13; INPUT READING TERMINATED NORMALLY Kapitel 6, Abschnitt 6.5.3, Mardias Tests auf multivariate Normalverteilung SUMMARY OF ANALYSIS Number of groups 1 Number of observations 238 Number of dependent variables 6 Number of independent variables 0 Number of continuous latent variables 1 Number of categorical latent variables 1 Observed dependent variables Continuous ITEM1 ITEM2 ITEM3 ITEM4 ITEM5 ITEM6 Continuous latent variables ETA Categorical latent variables C Estimator ML Information matrix OBSERVED Optimization Specifications for the Quasi-Newton Algorithm for Continuous Outcomes Maximum number of iterations 1000 Convergence criterion 0.500D-04 Optimization Specifications for the EM Algorithm Maximum number of iterations 500 Convergence criteria Loglikelihood change 0.100D-06 Relative loglikelihood change 0.100D-06 Derivative 0.100D-05 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-05 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-05 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 Input data file(s) daten-kapitel-6.dat Input data format FREE THE MODEL ESTIMATION TERMINATED NORMALLY MODEL FIT INFORMATION Number of Free Parameters 13 Loglikelihood H0 Value -435.870 Information Criteria Akaike (AIC) 897.740 Bayesian (BIC) 942.880 Sample-Size Adjusted BIC 901.674 (n* = (n + 2) / 24) FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASSES BASED ON THE ESTIMATED MODEL Latent Classes 1 238.00000 1.00000 FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS BASED ON ESTIMATED POSTERIOR PROBABILITIES Latent Classes 1 238.00000 1.00000 CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP Class Counts and Proportions Latent Classes 1 238 1.00000 Average Latent Class Probabilities for Most Likely Latent Class Membership (Row) by Latent Class (Column) 1 1 1.000 Classification Probabilities for the Most Likely Latent Class Membership (Row) by Latent Class (Column) 1 1 1.000 Logits for the Classification Probabilities for the Most Likely Latent Class Membership (Row) by Latent Class (Column) 1 1 0.000 MODEL RESULTS Two-Tailed Estimate S.E. Est./S.E. P-Value Latent Class 1 ETA BY ITEM1 1.000 0.000 999.000 999.000 ITEM2 1.000 0.000 999.000 999.000 ITEM3 1.000 0.000 999.000 999.000 ITEM4 1.000 0.000 999.000 999.000 ITEM5 1.000 0.000 999.000 999.000 ITEM6 1.000 0.000 999.000 999.000 Means ETA 0.000 0.000 999.000 999.000 Intercepts ITEM1 1.504 0.024 62.432 0.000 ITEM2 1.423 0.024 59.697 0.000 ITEM3 1.392 0.025 56.265 0.000 ITEM4 1.305 0.025 52.077 0.000 ITEM5 1.346 0.025 53.815 0.000 ITEM6 1.306 0.025 51.677 0.000 Variances ETA 0.064 0.007 8.985 0.000 Residual Variances ITEM1 0.074 0.008 9.238 0.000 ITEM2 0.071 0.008 9.178 0.000 ITEM3 0.081 0.009 9.402 0.000 ITEM4 0.085 0.009 9.453 0.000 ITEM5 0.085 0.009 9.449 0.000 ITEM6 0.088 0.009 9.510 0.000 QUALITY OF NUMERICAL RESULTS Condition Number for the Information Matrix 0.754E-02 (ratio of smallest to largest eigenvalue) TECHNICAL 13 OUTPUT SKEW AND KURTOSIS TESTS OF MODEL FIT ! Zweiseitiger Test, dass multivariate Schiefe der Normalverteilung entspricht TWO-SIDED MULTIVARIATE SKEW TEST OF FIT Sample Value 3.743 Mean 1.385 Standard Deviation 0.278 P-Value 0.0000 ! Zweiseitiger Test, dass multivariater Exzess der Normalverteilung entspricht TWO-SIDED MULTIVARIATE KURTOSIS TEST OF FIT Sample Value 52.680 Mean 47.724 Standard Deviation 1.108 P-Value 0.0000 ! Univariate Tests für Schiefe und Exzess UNIVARIATE SKEW AND KURTOSIS TESTS OF FIT Sample Standard Variable Value Mean Deviation P-Value TWO-SIDED UNIVARIATE SKEW TESTS OF FIT ITEM1 -0.458 0.011 0.152 0.0100 ITEM2 -0.179 0.001 0.149 0.2200 ITEM3 -0.042 -0.006 0.157 0.8200 ITEM4 0.105 0.003 0.147 0.4700 ITEM5 -0.086 0.005 0.166 0.5700 ITEM6 -0.079 -0.006 0.149 0.6000 TWO-SIDED UNIVARIATE KURTOSIS TESTS OF FIT ITEM1 0.768 -0.025 0.304 0.0200 ITEM2 0.833 -0.066 0.282 0.0200 ITEM3 0.426 -0.026 0.302 0.1400 ITEM4 0.868 -0.039 0.286 0.0000 ITEM5 0.602 0.000 0.332 0.1000 ITEM6 0.189 -0.062 0.311 0.3500 ! Bivariate Tests für Schiefe und Exzess BIVARIATE SKEW AND KURTOSIS TESTS OF FIT Sample Standard Variable pairs Value Mean Deviation P-Value TWO-SIDED BIVARIATE SKEW TESTS OF FIT ITEM1 AND ITEM2 0.656 0.090 0.063 0.0000 ITEM1 AND ITEM3 0.654 0.096 0.068 0.0000 ITEM1 AND ITEM4 0.733 0.100 0.076 0.0000 ITEM1 AND ITEM5 0.691 0.100 0.072 0.0000 ITEM1 AND ITEM6 0.501 0.092 0.072 0.0000 ITEM2 AND ITEM3 0.591 0.098 0.073 0.0000 ITEM2 AND ITEM4 0.741 0.091 0.067 0.0000 ITEM2 AND ITEM5 0.673 0.098 0.075 0.0000 ITEM2 AND ITEM6 0.396 0.094 0.070 0.0100 ITEM3 AND ITEM4 0.591 0.098 0.072 0.0000 ITEM3 AND ITEM5 0.559 0.107 0.087 0.0100 ITEM3 AND ITEM6 0.435 0.097 0.070 0.0000 ITEM4 AND ITEM5 1.007 0.103 0.076 0.0000 ITEM4 AND ITEM6 0.455 0.093 0.067 0.0000 ITEM5 AND ITEM6 0.289 0.107 0.095 0.0900 TWO-SIDED BIVARIATE KURTOSIS TESTS OF FIT ITEM1 AND ITEM2 9.675 7.924 0.485 0.0200 ITEM1 AND ITEM3 9.021 7.945 0.447 0.0600 ITEM1 AND ITEM4 9.655 7.948 0.451 0.0000 ITEM1 AND ITEM5 9.878 8.022 0.550 0.0100 ITEM1 AND ITEM6 9.176 7.961 0.522 0.0500 ITEM2 AND ITEM3 9.502 7.939 0.504 0.0200 ITEM2 AND ITEM4 9.805 7.950 0.514 0.0000 ITEM2 AND ITEM5 9.826 7.973 0.482 0.0000 ITEM2 AND ITEM6 9.360 7.912 0.466 0.0100 ITEM3 AND ITEM4 9.912 7.973 0.500 0.0100 ITEM3 AND ITEM5 8.984 8.046 0.523 0.0900 ITEM3 AND ITEM6 8.856 7.957 0.518 0.1000 ITEM4 AND ITEM5 9.695 7.998 0.489 0.0000 ITEM4 AND ITEM6 9.089 7.913 0.471 0.0400 ITEM5 AND ITEM6 9.265 8.006 0.537 0.0500 DIAGRAM INFORMATION Mplus diagrams are currently not available for Mixture analysis. No diagram output was produced. Beginning Time: 09:34:15 Ending Time: 09:34:16 Elapsed Time: 00:00:01 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) 1998-2013 Muthen & Muthen