Mplus VERSION 7
MUTHEN & MUTHEN
09/22/2012  10:55 PM

INPUT INSTRUCTIONS

  TITLE:	this is an example of a piecewise growth
  	model for a continuous outcome
  DATA:	FILE IS ex6.11.dat;
  VARIABLE:	NAMES ARE y1-y5;	
  MODEL:	i s1 | y1@0 y2@1 y3@2 y4@2 y5@2;
  	i s2 | y1@0 y2@0 y3@0 y4@1 y5@2;



INPUT READING TERMINATED NORMALLY



this is an example of a piecewise growth
model for a continuous outcome

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                         500

Number of dependent variables                                    5
Number of independent variables                                  0
Number of continuous latent variables                            3

Observed dependent variables

  Continuous
   Y1          Y2          Y3          Y4          Y5

Continuous latent variables
   I           S1          S2


Estimator                                                       ML
Information matrix                                        OBSERVED
Maximum number of iterations                                  1000
Convergence criterion                                    0.500D-04
Maximum number of steepest descent iterations                   20

Input data file(s)
  ex6.11.dat

Input data format  FREE



THE MODEL ESTIMATION TERMINATED NORMALLY



MODEL FIT INFORMATION

Number of Free Parameters                       14

Loglikelihood

          H0 Value                       -3706.171
          H1 Value                       -3703.549

Information Criteria

          Akaike (AIC)                    7440.342
          Bayesian (BIC)                  7499.346
          Sample-Size Adjusted BIC        7454.909
            (n* = (n + 2) / 24)

Chi-Square Test of Model Fit

          Value                              5.244
          Degrees of Freedom                     6
          P-Value                           0.5130

RMSEA (Root Mean Square Error Of Approximation)

          Estimate                           0.000
          90 Percent C.I.                    0.000  0.054
          Probability RMSEA <= .05           0.929

CFI/TLI

          CFI                                1.000
          TLI                                1.001

Chi-Square Test of Model Fit for the Baseline Model

          Value                           1587.697
          Degrees of Freedom                    10
          P-Value                           0.0000

SRMR (Standardized Root Mean Square Residual)

          Value                              0.010



MODEL RESULTS

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

 I        |
    Y1                 1.000      0.000    999.000    999.000
    Y2                 1.000      0.000    999.000    999.000
    Y3                 1.000      0.000    999.000    999.000
    Y4                 1.000      0.000    999.000    999.000
    Y5                 1.000      0.000    999.000    999.000

 S1       |
    Y1                 0.000      0.000    999.000    999.000
    Y2                 1.000      0.000    999.000    999.000
    Y3                 2.000      0.000    999.000    999.000
    Y4                 2.000      0.000    999.000    999.000
    Y5                 2.000      0.000    999.000    999.000

 S2       |
    Y1                 0.000      0.000    999.000    999.000
    Y2                 0.000      0.000    999.000    999.000
    Y3                 0.000      0.000    999.000    999.000
    Y4                 1.000      0.000    999.000    999.000
    Y5                 2.000      0.000    999.000    999.000

 S1       WITH
    I                 -0.029      0.049     -0.589      0.556

 S2       WITH
    I                  0.059      0.036      1.642      0.101
    S1                -0.031      0.026     -1.184      0.237

 Means
    I                  0.462      0.052      8.955      0.000
    S1                 1.071      0.030     35.945      0.000
    S2                 1.957      0.030     64.314      0.000

 Intercepts
    Y1                 0.000      0.000    999.000    999.000
    Y2                 0.000      0.000    999.000    999.000
    Y3                 0.000      0.000    999.000    999.000
    Y4                 0.000      0.000    999.000    999.000
    Y5                 0.000      0.000    999.000    999.000

 Variances
    I                  0.985      0.100      9.827      0.000
    S1                 0.240      0.037      6.408      0.000
    S2                 0.219      0.042      5.265      0.000

 Residual Variances
    Y1                 0.394      0.077      5.156      0.000
    Y2                 0.525      0.043     12.185      0.000
    Y3                 0.501      0.068      7.354      0.000
    Y4                 0.483      0.048     10.089      0.000
    Y5                 0.559      0.103      5.424      0.000


QUALITY OF NUMERICAL RESULTS

     Condition Number for the Information Matrix              0.136E-01
       (ratio of smallest to largest eigenvalue)


     Beginning Time:  22:55:46
        Ending Time:  22:55:46
       Elapsed Time:  00:00:00



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