Mplus VERSION 7
MUTHEN & MUTHEN
09/22/2012  11:35 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a two-level SEM with categorical
  factor indicators on the within level and cluster-level
  continuous observed and random intercept factor indicators
  on the between level
  DATA:   	FILE IS ex9.9.dat;
  VARIABLE:	NAMES ARE u1-u6 y1-y4 x1 x2 w clus;
  	CATEGORICAL = u1-u6;
  	WITHIN = x1 x2;
           	BETWEEN = w y1-y4;
            	CLUSTER IS clus;
  ANALYSIS:	TYPE IS TWOLEVEL;
  	ESTIMATOR = WLSMV;
  MODEL:
  	%WITHIN%
  	fw1 BY u1-u3;
  	fw2 BY u4-u6;
  	fw1 fw2 ON x1 x2;
  	%BETWEEN%
  	fb BY u1-u6;
  	f BY y1-y4;
  	fb ON w f;
  	f ON w;
  SAVEDATA:	SWMATRIX = ex9.9sw.dat;



INPUT READING TERMINATED NORMALLY



this is an example of a two-level SEM with categorical
factor indicators on the within level and cluster-level
continuous observed and random intercept factor indicators
on the between level

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        1000

Number of dependent variables                                   10
Number of independent variables                                  3
Number of continuous latent variables                            4

Observed dependent variables

  Continuous
   Y1          Y2          Y3          Y4

  Binary and ordered categorical (ordinal)
   U1          U2          U3          U4          U5          U6

Observed independent variables
   X1          X2          W

Continuous latent variables
   FW1         FW2         FB          F

Variables with special functions

  Cluster variable      CLUS

  Within variables
   X1          X2

  Between variables
   Y1          Y2          Y3          Y4          W


Estimator                                                    WLSMV
Optimization Specifications for the Quasi-Newton Algorithm for
Continuous Outcomes
  Maximum number of iterations                                1000
  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                            10
  Minimum value for logit thresholds                           -10
  Minimum expected cell size for chi-square              0.100D-01
Optimization algorithm                                      EMA/FS
Integration Specifications
  Type                                                    STANDARD
  Number of integration points                                   7
  Dimensions of numerical integration                            0
  Adaptive quadrature                                           ON
Link                                                        PROBIT
Cholesky                                                        ON

Input data file(s)
  ex9.9.dat
Input data format  FREE


SUMMARY OF DATA

     Number of clusters                        110

     Average cluster size        9.091

     Estimated Intraclass Correlations for the Y Variables

                Intraclass              Intraclass              Intraclass
     Variable  Correlation   Variable  Correlation   Variable  Correlation

     U1           0.376      U2           0.259      U3           0.310
     U4           0.309      U5           0.317      U6           0.282



UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    U1
      Category 1    0.476      476.000
      Category 2    0.524      524.000
    U2
      Category 1    0.447      447.000
      Category 2    0.553      553.000
    U3
      Category 1    0.473      473.000
      Category 2    0.527      527.000
    U4
      Category 1    0.479      479.000
      Category 2    0.521      521.000
    U5
      Category 1    0.490      490.000
      Category 2    0.510      510.000
    U6
      Category 1    0.513      513.000
      Category 2    0.487      487.000



     THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                       44

Chi-Square Test of Model Fit

          Value                             69.697*
          Degrees of Freedom                    58
          P-Value                           0.1397

*   The chi-square value for MLM, MLMV, MLR, ULSMV, WLSM and WLSMV cannot be used
    for chi-square difference testing in the regular way.  MLM, MLR and WLSM
    chi-square difference testing is described on the Mplus website.  MLMV, WLSMV,
    and ULSMV difference testing is done using the DIFFTEST option.

RMSEA (Root Mean Square Error Of Approximation)

          Estimate                           0.014

CFI/TLI

          CFI                                0.990
          TLI                                0.986

Chi-Square Test of Model Fit for the Baseline Model

          Value                           1225.492
          Degrees of Freedom                    82
          P-Value                           0.0000

SRMR (Standardized Root Mean Square Residual)

          Value for Within                   0.044
          Value for Between                  0.084

WRMR (Weighted Root Mean Square Residual)

          Value                              0.621



MODEL RESULTS

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

Within Level

 FW1      BY
    U1                 1.000      0.000    999.000    999.000
    U2                 0.827      0.146      5.653      0.000
    U3                 1.029      0.200      5.139      0.000

 FW2      BY
    U4                 1.000      0.000    999.000    999.000
    U5                 1.113      0.198      5.609      0.000
    U6                 0.952      0.136      6.983      0.000

 FW1        ON
    X1                 0.525      0.073      7.152      0.000
    X2                 0.694      0.098      7.091      0.000

 FW2        ON
    X1                 0.692      0.091      7.640      0.000
    X2                 0.559      0.077      7.226      0.000

 FW2      WITH
    FW1               -0.034      0.079     -0.430      0.667

 Residual Variances
    FW1                1.157      0.303      3.822      0.000
    FW2                1.240      0.266      4.664      0.000

Between Level

 FB       BY
    U1                 1.000      0.000    999.000    999.000
    U2                 0.798      0.135      5.928      0.000
    U3                 1.007      0.172      5.836      0.000
    U4                 1.062      0.182      5.836      0.000
    U5                 1.050      0.205      5.120      0.000
    U6                 0.845      0.163      5.181      0.000

 F        BY
    Y1                 1.000      0.000    999.000    999.000
    Y2                 1.225      0.246      4.972      0.000
    Y3                 0.901      0.200      4.507      0.000
    Y4                 1.412      0.268      5.260      0.000

 FB         ON
    F                  0.873      0.243      3.588      0.000

 FB         ON
    W                  1.003      0.160      6.283      0.000

 F          ON
    W                  0.259      0.078      3.307      0.001

 Intercepts
    Y1                 0.063      0.084      0.741      0.459
    Y2                -0.056      0.095     -0.590      0.555
    Y3                -0.048      0.091     -0.528      0.598
    Y4                -0.010      0.107     -0.093      0.926

 Thresholds
    U1$1              -0.118      0.137     -0.863      0.388
    U2$1              -0.232      0.106     -2.190      0.029
    U3$1              -0.168      0.130     -1.289      0.197
    U4$1              -0.128      0.124     -1.032      0.302
    U5$1              -0.107      0.137     -0.780      0.435
    U6$1               0.103      0.118      0.880      0.379

 Residual Variances
    U1                 0.612      0.235      2.601      0.009
    U2                 0.189      0.124      1.516      0.130
    U3                 0.302      0.162      1.861      0.063
    U4                 0.224      0.131      1.719      0.086
    U5                 0.416      0.210      1.985      0.047
    U6                 0.344      0.143      2.397      0.017
    Y1                 0.447      0.077      5.823      0.000
    Y2                 0.464      0.095      4.891      0.000
    Y3                 0.606      0.104      5.823      0.000
    Y4                 0.415      0.099      4.201      0.000
    FB                 0.439      0.143      3.065      0.002
    F                  0.328      0.097      3.371      0.001


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.124E-02
       (ratio of smallest to largest eigenvalue)


SAVEDATA INFORMATION


  Within and between sample statistics with Weight matrix

  Save file
    ex9.9sw.dat
  Save format      Free

     Beginning Time:  23:35:01
        Ending Time:  23:35:08
       Elapsed Time:  00:00:07



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