Mplus VERSION 7
MUTHEN & MUTHEN
09/22/2012  11:18 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a two-level multiple
  	indicator growth model with categorical
  	outcomes (three-level analysis)
  DATA:	FILE IS ex9.15.dat;
  VARIABLE:	NAMES ARE u11 u21 u31 u12 u22 u32 u13 u23
  	u33 clus;
  	CATEGORICAL = u11-u33;
  	CLUSTER = clus;
  ANALYSIS:	TYPE IS TWOLEVEL;
  	ESTIMATOR = WLSM;
  MODEL:
  	%WITHIN%	
  	f1w BY	u11
  	u21-u31 (1-2);	
  	f2w BY u12
  	u22-u32 (1-2);
  	f3w BY u13
  	u23-u33 (1-2);
  	iw sw | f1w@0 f2w@1 f3w@2;
  	%BETWEEN%	
  	f1b BY	u11
  	u21-u31 (1-2);	
  	f2b BY u12
  	u22-u32 (1-2);
  	f3b BY u13
  	u23-u33 (1-2);
  	[u11$1 u12$1 u13$1] (3);
  	[u21$1 u22$1 u23$1] (4);
  	[u31$1 u32$1 u33$1] (5);
  	ib sb | f1b@0 f2b@1 f3b@2;
  	[f1b-f3b@0 ib@0 sb];
  	f1b-f3b (6);
  SAVEDATA:	SWMATRIX = ex9.15sw.dat;



INPUT READING TERMINATED NORMALLY



this is an example of a two-level multiple
indicator growth model with categorical
outcomes (three-level analysis)

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                         500

Number of dependent variables                                    9
Number of independent variables                                  0
Number of continuous latent variables                           10

Observed dependent variables

  Binary and ordered categorical (ordinal)
   U11         U21         U31         U12         U22         U32
   U13         U23         U33

Continuous latent variables
   F1W         F2W         F3W         IW          SW          F1B
   F2B         F3B         IB          SB

Variables with special functions

  Cluster variable      CLUS

Estimator                                                     WLSM
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                                          FS
Integration Specifications
  Type                                                    STANDARD
  Number of integration points                                   7
  Dimensions of numerical integration                            2
  Adaptive quadrature                                           ON
Link                                                        PROBIT
Cholesky                                                        ON

Input data file(s)
  ex9.15.dat
Input data format  FREE


SUMMARY OF DATA

     Number of clusters                         90

     Average cluster size        5.556

     Estimated Intraclass Correlations for the Y Variables

                Intraclass              Intraclass              Intraclass
     Variable  Correlation   Variable  Correlation   Variable  Correlation

     U11          0.493      U21          0.203      U31          0.421
     U12          0.270      U22          0.341      U32          0.360
     U13          0.434      U23          0.426      U33          0.397



UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES

    U11
      Category 1    0.534      267.000
      Category 2    0.466      233.000
    U21
      Category 1    0.386      193.000
      Category 2    0.614      307.000
    U31
      Category 1    0.622      311.000
      Category 2    0.378      189.000
    U12
      Category 1    0.282      141.000
      Category 2    0.718      359.000
    U22
      Category 1    0.242      121.000
      Category 2    0.758      379.000
    U32
      Category 1    0.448      224.000
      Category 2    0.552      276.000
    U13
      Category 1    0.184       92.000
      Category 2    0.816      408.000
    U23
      Category 1    0.160       80.000
      Category 2    0.840      420.000
    U33
      Category 1    0.314      157.000
      Category 2    0.686      343.000



     THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                       25

Chi-Square Test of Model Fit

          Value                             70.639*
          Degrees of Freedom                    65
          P-Value                           0.2949
          Scaling Correction Factor         0.6909
            for WLSM

*   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                           0.013

CFI/TLI

          CFI                                0.996
          TLI                                0.995

Chi-Square Test of Model Fit for the Baseline Model

          Value                           1354.865
          Degrees of Freedom                    72
          P-Value                           0.0000

SRMR (Standardized Root Mean Square Residual)

          Value for Within                   0.060
          Value for Between                  0.168

WRMR (Weighted Root Mean Square Residual)

          Value                              0.736



MODEL RESULTS

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

Within Level

 IW       |
    F1W                1.000      0.000    999.000    999.000
    F2W                1.000      0.000    999.000    999.000
    F3W                1.000      0.000    999.000    999.000

 SW       |
    F1W                0.000      0.000    999.000    999.000
    F2W                1.000      0.000    999.000    999.000
    F3W                2.000      0.000    999.000    999.000

 F1W      BY
    U11                1.000      0.000    999.000    999.000
    U21                0.900      0.162      5.572      0.000
    U31                0.756      0.128      5.924      0.000

 F2W      BY
    U12                1.000      0.000    999.000    999.000
    U22                0.900      0.162      5.572      0.000
    U32                0.756      0.128      5.924      0.000

 F3W      BY
    U13                1.000      0.000    999.000    999.000
    U23                0.900      0.162      5.572      0.000
    U33                0.756      0.128      5.924      0.000

 SW       WITH
    IW                -0.287      0.238     -1.203      0.229

 Variances
    IW                 1.724      0.607      2.842      0.004
    SW                 0.351      0.234      1.500      0.134

 Residual Variances
    F1W                1.134      0.639      1.775      0.076
    F2W                0.548      0.375      1.459      0.145
    F3W                0.746      0.658      1.134      0.257

Between Level

 IB       |
    F1B                1.000      0.000    999.000    999.000
    F2B                1.000      0.000    999.000    999.000
    F3B                1.000      0.000    999.000    999.000

 SB       |
    F1B                0.000      0.000    999.000    999.000
    F2B                1.000      0.000    999.000    999.000
    F3B                2.000      0.000    999.000    999.000

 F1B      BY
    U11                1.000      0.000    999.000    999.000
    U21                0.900      0.162      5.572      0.000
    U31                0.756      0.128      5.924      0.000

 F2B      BY
    U12                1.000      0.000    999.000    999.000
    U22                0.900      0.162      5.572      0.000
    U32                0.756      0.128      5.924      0.000

 F3B      BY
    U13                1.000      0.000    999.000    999.000
    U23                0.900      0.162      5.572      0.000
    U33                0.756      0.128      5.924      0.000

 SB       WITH
    IB                -0.147      0.192     -0.765      0.444

 Means
    IB                 0.000      0.000    999.000    999.000
    SB                 1.044      0.189      5.523      0.000

 Intercepts
    F1B                0.000      0.000    999.000    999.000
    F2B                0.000      0.000    999.000    999.000
    F3B                0.000      0.000    999.000    999.000

 Thresholds
    U11$1             -0.079      0.185     -0.431      0.667
    U21$1             -0.534      0.154     -3.467      0.001
    U31$1              0.566      0.151      3.756      0.000
    U12$1             -0.079      0.185     -0.431      0.667
    U22$1             -0.534      0.154     -3.467      0.001
    U32$1              0.566      0.151      3.756      0.000
    U13$1             -0.079      0.185     -0.431      0.667
    U23$1             -0.534      0.154     -3.467      0.001
    U33$1              0.566      0.151      3.756      0.000

 Variances
    IB                 0.580      0.356      1.628      0.103
    SB                 0.293      0.223      1.313      0.189

 Residual Variances
    U11                2.774      1.239      2.238      0.025
    U21                0.061      0.320      0.191      0.849
    U31                1.357      0.479      2.834      0.005
    U12                0.157      0.380      0.413      0.680
    U22                0.593      0.477      1.242      0.214
    U32                0.668      0.332      2.013      0.044
    U13                1.297      1.130      1.148      0.251
    U23                1.122      0.742      1.512      0.130
    U33                0.799      0.456      1.753      0.080
    F1B                0.390      0.186      2.094      0.036
    F2B                0.390      0.186      2.094      0.036
    F3B                0.390      0.186      2.094      0.036


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.337E-03
       (ratio of smallest to largest eigenvalue)


SAVEDATA INFORMATION


  Within and between sample statistics with Weight matrix

  Save file
    ex9.15sw.dat
  Save format      Free

     Beginning Time:  23:18:20
        Ending Time:  23:18:27
       Elapsed Time:  00:00:07



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