Output from calis65.sas	Source 0 Graphs

                     CALIS65: Special LISREL Application                     1
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

          Covariance Structure Analysis: Pattern and Initial Values

              LINEQS Model Statement
         -------------------------------
              Matrix         Rows & Cols          Matrix Type

 TERM   1-----------------------------------------------------------
           1    _SEL_          5      10    SELECTION
           2    _BETA_        10      10    EQSBETA        IMINUSINV
           3    _GAMMA_       10       5    EQSGAMMA
           4    _PHI_          5       5    SYMMETRIC

     Number of endogenous variables = 5

Manifest:     VAR1      VAR2      VAR3      VAR4      VAR5

     Number of exogenous variables = 5

Error:        E1        E2        E3        E4        E5

                     CALIS65: Special LISREL Application                     2
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

          Covariance Structure Analysis: Pattern and Initial Values

                         Manifest Variable Equations
                              Initial Estimates

                           VAR1    =    1.0000 E1

                           VAR2    =    1.0000 E2

                           VAR3    =    1.0000 E3

                           VAR4    =    1.0000 E4

                           VAR5    =    1.0000 E5

                      Variances of Exogenous Variables
                    -------------------------------------
                    Variable    Parameter      Estimate
                    -------------------------------------

                    E1                           1.000000
                    E2                           1.000000
                    E3                           1.000000
                    E4                           1.000000
                    E5                           1.000000

                    Covariances among Exogenous Variables
                     -----------------------------------
                          Parameter           Estimate
                     -----------------------------------

                     E2      E1      RO1               .
                     E3      E1      RO2               .
                     E3      E2      RO2               .
                     E4      E1      RO2               .
                     E4      E2      RO2               .
                     E4      E3      RO3               .
                     E5      E1      RO2               .
                     E5      E2      RO2               .
                     E5      E3      RO3               .
                     E5      E4      RO3               .

                     CALIS65: Special LISREL Application                     3
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

          Covariance Structure Analysis: Pattern and Initial Values

                                Weight Matrix

              _V001001      _V002001      _V002002      _V003001      _V003002

_V001001       0.00100       0.00000       0.00000       0.00000       0.00000
_V002001       0.00000       0.79647       0.00000       0.47447       0.41063
_V002002       0.00000       0.00000       0.00100       0.00000       0.00000
_V003001       0.00000       0.47447       0.00000       0.78243       0.43580
_V003002       0.00000       0.41063       0.00000       0.43580       0.70375
_V003003       0.00000       0.00000       0.00000       0.00000       0.00000
_V004001       0.00000       0.62800       0.00000       0.50016       0.47655
_V004002       0.00000       0.54377       0.00000       0.50631       0.56329
_V004003       0.00000       0.44737       0.00000       0.46244       0.46039
_V004004       0.00000       0.00000       0.00000       0.00000       0.00000
_V005001       0.00000       0.41962       0.00000       0.30358       0.27423
_V005002       0.00000       0.26180       0.00000       0.21433       0.15751
_V005003       0.00000       0.33925       0.00000       0.34469       0.44414
_V005004       0.00000       0.24254       0.00000       0.24259       0.22342
_V005005       0.00000       0.00000       0.00000       0.00000       0.00000


              _V003003      _V004001      _V004002      _V004003      _V004004

_V001001       0.00000        0.0000        0.0000        0.0000       0.00000
_V002001       0.00000        0.6280        0.5438        0.4474       0.00000
_V002002       0.00000        0.0000        0.0000        0.0000       0.00000
_V003001       0.00000        0.5002        0.5063        0.4624       0.00000
_V003002       0.00000        0.4766        0.5633        0.4604       0.00000
_V003003       0.00100        0.0000        0.0000        0.0000       0.00000
_V004001       0.00000        1.6174        0.9240        0.7949       0.00000
_V004002       0.00000        0.9240        1.3570        0.6964       0.00000
_V004003       0.00000        0.7949        0.6964        1.0331       0.00000
_V004004       0.00000        0.0000        0.0000        0.0000       0.00100
_V005001       0.00000        0.5082        0.3377        0.3309       0.00000
_V005002       0.00000        0.2537        0.2902        0.2031       0.00000
_V005003       0.00000        0.3760        0.3646        0.4260       0.00000
_V005004       0.00000        0.4423        0.3913        0.3625       0.00000
_V005005       0.00000        0.0000        0.0000        0.0000       0.00000

                     CALIS65: Special LISREL Application                     4
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

          Covariance Structure Analysis: Pattern and Initial Values

                                Weight Matrix

              _V005001      _V005002      _V005003      _V005004      _V005005

_V001001       0.00000       0.00000       0.00000       0.00000       0.00000
_V002001       0.41962       0.26180       0.33925       0.24254       0.00000
_V002002       0.00000       0.00000       0.00000       0.00000       0.00000
_V003001       0.30358       0.21433       0.34469       0.24259       0.00000
_V003002       0.27423       0.15751       0.44414       0.22342       0.00000
_V003003       0.00000       0.00000       0.00000       0.00000       0.00000
_V004001       0.50823       0.25366       0.37601       0.44226       0.00000
_V004002       0.33768       0.29020       0.36461       0.39126       0.00000
_V004003       0.33087       0.20313       0.42595       0.36247       0.00000
_V004004       0.00000       0.00000       0.00000       0.00000       0.00000
_V005001       0.80230       0.28610       0.41127       0.31492       0.00000
_V005002       0.28610       0.49805       0.35162       0.20440       0.00000
_V005003       0.41127       0.35162       0.91267       0.34705       0.00000
_V005004       0.31492       0.20440       0.34705       0.64995       0.00000
_V005005       0.00000       0.00000       0.00000       0.00000       0.00100
                  Determinant of Weight Matrix 2.183019E-18

                     CALIS65: Special LISREL Application                     5
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

       Covariance Structure Analysis: Weighted Least-Squares Estimation

                   200 Observations       Model Terms          1
                     5 Variables          Model Matrices       4
                    15 Informations       Parameters           3

                 VARIABLE              Mean           Std Dev

                 VAR1                     0       1.000000000
                 VAR2                     0       1.000000000
                 VAR3                     0       1.000000000
                 VAR4                     0       1.000000000
                 VAR5                     0       1.000000000

                                 Correlations

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       1.0000       0.5264       0.4021       0.3910       0.4169
    VAR2       0.5264       1.0000       0.4819       0.4236       0.4889
    VAR3       0.4021       0.4819       1.0000       0.3997       0.2743
    VAR4       0.3910       0.4236       0.3997       1.0000       0.4417
    VAR5       0.4169       0.4889       0.2743       0.4417       1.0000
                      Determinant = 0.2681 (Ln = -1.316)

                         Vector of Initial Estimates

 RO1           1    0.52639  Matrix Entry: _PHI_[2:1]
 RO2           2    0.43408  Matrix Entry: _PHI_[3:1] _PHI_[3:2] _PHI_[4:1]
                                           _PHI_[4:2] _PHI_[5:1] _PHI_[5:2]
 RO3           3    0.37193  Matrix Entry: _PHI_[4:3] _PHI_[5:3] _PHI_[5:4]

            Predetermined Elements of the Predicted Moment Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       1.0000        .            .            .            .
    VAR2        .           1.0000        .            .            .
    VAR3        .            .           1.0000        .            .
    VAR4        .            .            .           1.0000        .
    VAR5        .            .            .            .           1.0000
                        Sum of Squared Differences = 0

NOTE: The degrees of freedom are reduced by 5.

                     CALIS65: Special LISREL Application                     6
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

       Covariance Structure Analysis: Weighted Least-Squares Estimation

                       Levenberg-Marquardt Optimization
                        Scaling Update of More (1978)
                       Number of Parameter Estimates 3
                    Number of Functions (Observations) 15

Optimization Start: Active Constraints= 0  Criterion= 0.103
Maximum Gradient Element= 0.305 Radius= 1.000

        Iter rest nfun act   optcrit  difcrit maxgrad  lambda     rho

           1    0    2   0    0.0820   0.0209 283E-18       0   2.000

Optimization Results: Iterations= 1 Function Calls= 3 Jacobian Calls= 2
Active Constraints= 0  Criterion= 0.08196817
Maximum Gradient Element= 2.83438E-16 Lambda= 0 Rho= 2 Radius= 0.6105

NOTE:  ABSGCONV convergence criterion satisfied.

                     CALIS65: Special LISREL Application                     7
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

       Covariance Structure Analysis: Weighted Least-Squares Estimation

                            Predicted Model Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       1.0000       0.6035       0.5135       0.5135       0.5135
    VAR2       0.6035       1.0000       0.5135       0.5135       0.5135
    VAR3       0.5135       0.5135       1.0000       0.4288       0.4288
    VAR4       0.5135       0.5135       0.4288       1.0000       0.4288
    VAR5       0.5135       0.5135       0.4288       0.4288       1.0000
                      Determinant = 0.1807 (Ln = -1.711)

                     CALIS65: Special LISREL Application                     8
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

       Covariance Structure Analysis: Weighted Least-Squares Estimation

         Fit criterion . . . . . . . . . . . . . . . . . .     0.0820
         Goodness of Fit Index (GFI) . . . . . . . . . . .     1.0000
         GFI Adjusted for Degrees of Freedom (AGFI). . . .     1.0000
         Root Mean Square Residual (RMR) . . . . . . . . .     0.0717
         Parsimonious GFI (Mulaik, 1989) . . . . . . . . .     0.7000
         Chi-square = 16.3117       df = 7       Prob>chi**2 = 0.0224
         Null Model Chi-square:     df = 10                  191.1599
         RMSEA Estimate  . . . . . .  0.0818  90%C.I.[0.0289, 0.1343]
         Probability of Close Fit  . . . . . . . . . . . .     0.1349
         ECVI Estimate . . . . . . .  0.1121  90%C.I.[0.0963, 0.2167]
         Bentler's Comparative Fit Index . . . . . . . . .     0.9486
         Akaike's Information Criterion. . . . . . . . . .     2.3117
         Bozdogan's (1987) CAIC. . . . . . . . . . . . . .   -27.7766
         Schwarz's Bayesian Criterion. . . . . . . . . . .   -20.7766
         McDonald's (1989) Centrality. . . . . . . . . . .     0.9770
         Bentler & Bonett's (1980) Non-normed Index. . . .     0.9266
         Bentler & Bonett's (1980) NFI . . . . . . . . . .     0.9147
         James, Mulaik, & Brett (1982) Parsimonious NFI. .     0.6403
         Z-Test of Wilson & Hilferty (1931). . . . . . . .     2.0065
         Bollen (1986) Normed Index Rho1 . . . . . . . . .     0.8781
         Bollen (1988) Non-normed Index Delta2 . . . . . .     0.9494
         Hoelter's (1983) Critical N . . . . . . . . . . .        173

                               Residual Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1      0.00000      -.07710      -.11133      -.12250      -.09654
    VAR2      -.07710      0.00000      -.03160      -.08983      -.02453
    VAR3      -.11133      -.03160      0.00000      -.02903      -.15448
    VAR4      -.12250      -.08983      -.02903      0.00000      0.01298
    VAR5      -.09654      -.02453      -.15448      0.01298      0.00000
                     Average Absolute Residual = 0.04999
               Average Off-diagonal Absolute Residual = 0.07499

                      Rank Order of 7 Largest Residuals

  VAR5,VAR3  VAR4,VAR1  VAR3,VAR1  VAR5,VAR1  VAR4,VAR2  VAR2,VAR1  VAR3,VAR2
   -0.15448   -0.12250   -0.11133   -0.09654   -0.08983   -0.07710   -0.03160

                     CALIS65: Special LISREL Application                     9
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

       Covariance Structure Analysis: Weighted Least-Squares Estimation

                 Asymptotically Standardized Residual Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       0.0000      -2.8603      -2.2874      -1.5119      -1.9430
    VAR2      -2.8603       0.0000      -0.7113      -1.2390      -0.8003
    VAR3      -2.2874      -0.7113       0.0000      -0.5370      -3.2093
    VAR4      -1.5119      -1.2390      -0.5370       0.0000       0.4110
    VAR5      -1.9430      -0.8003      -3.2093       0.4110       0.0000
                    Average Standardized Residual = 1.034
              Average Off-diagonal Standardized Residual = 1.551

        Rank Order of 7 Largest Asymptotically Standardized Residuals

  VAR5,VAR3  VAR2,VAR1  VAR3,VAR1  VAR5,VAR1  VAR4,VAR1  VAR4,VAR2  VAR5,VAR2
   -3.20927   -2.86029   -2.28745   -1.94302   -1.51195   -1.23903   -0.80028

            Distribution of Asymptotically Standardized Residuals
                       (Each * represents 1 residuals)

                    -3.25000 -   -3.00000  1   6.67% | *
                    -3.00000 -   -2.75000  1   6.67% | *
                    -2.75000 -   -2.50000  0   0.00% |
                    -2.50000 -   -2.25000  1   6.67% | *
                    -2.25000 -   -2.00000  0   0.00% |
                    -2.00000 -   -1.75000  1   6.67% | *
                    -1.75000 -   -1.50000  1   6.67% | *
                    -1.50000 -   -1.25000  0   0.00% |
                    -1.25000 -   -1.00000  1   6.67% | *
                    -1.00000 -   -0.75000  1   6.67% | *
                    -0.75000 -   -0.50000  2  13.33% | **
                    -0.50000 -   -0.25000  0   0.00% |
                    -0.25000 -          0  0   0.00% |
                           0 -    0.25000  5  33.33% | *****
                     0.25000 -    0.50000  1   6.67% | *

                     CALIS65: Special LISREL Application                    10
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

       Covariance Structure Analysis: Weighted Least-Squares Estimation

                         Manifest Variable Equations

                           VAR1    =    1.0000 E1

                           VAR2    =    1.0000 E2

                           VAR3    =    1.0000 E3

                           VAR4    =    1.0000 E4

                           VAR5    =    1.0000 E5

                      Variances of Exogenous Variables
    ---------------------------------------------------------------------
                                               Standard
    Variable    Parameter      Estimate          Error          t Value
    ---------------------------------------------------------------------

    E1                           1.000000               0           0.000
    E2                           1.000000               0           0.000
    E3                           1.000000               0           0.000
    E4                           1.000000               0           0.000
    E5                           1.000000               0           0.000

                    Covariances among Exogenous Variables
     -------------------------------------------------------------------
                                              Standard
          Parameter           Estimate          Error          t Value
     -------------------------------------------------------------------

     E2      E1      RO1        0.603483        0.057235          10.544
     E3      E1      RO2        0.513469        0.039535          12.988
     E3      E2      RO2        0.513469        0.039535          12.988
     E4      E1      RO2        0.513469        0.039535          12.988
     E4      E2      RO2        0.513469        0.039535          12.988
     E4      E3      RO3        0.428771        0.047638           9.001
     E5      E1      RO2        0.513469        0.039535          12.988
     E5      E2      RO2        0.513469        0.039535          12.988
     E5      E3      RO3        0.428771        0.047638           9.001
     E5      E4      RO3        0.428771        0.047638           9.001

                     CALIS65: Special LISREL Application                    11
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

       Covariance Structure Analysis: Weighted Least-Squares Estimation

                   Equations with Standardized Coefficients

                           VAR1    =    1.0000 E1

                           VAR2    =    1.0000 E2

                           VAR3    =    1.0000 E3

                           VAR4    =    1.0000 E4

                           VAR5    =    1.0000 E5

                         Squared Multiple Correlations
         ------------------------------------------------------------
                             Error           Total
           Variable        Variance        Variance        R-squared
         ------------------------------------------------------------

            1    VAR1        1.000000        1.000000               0
            2    VAR2        1.000000        1.000000               0
            3    VAR3        1.000000        1.000000               0
            4    VAR4        1.000000        1.000000               0
            5    VAR5        1.000000        1.000000               0

                    Correlations among Exogenous Variables
                     -----------------------------------
                          Parameter           Estimate
                     -----------------------------------

                     E2      E1      RO1        0.603483
                     E3      E1      RO2        0.513469
                     E3      E2      RO2        0.513469
                     E4      E1      RO2        0.513469
                     E4      E2      RO2        0.513469
                     E4      E3      RO3        0.428771
                     E5      E1      RO2        0.513469
                     E5      E2      RO2        0.513469
                     E5      E3      RO3        0.428771
                     E5      E4      RO3        0.428771

                     CALIS65: Special LISREL Application                    12
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

       Covariance Structure Analysis: Weighted Least-Squares Estimation

             Lagrange Multiplier and Wald Test Indices _PHI_[5:5]
                               Symmetric Matrix
                  Univariate Tests for Constant Constraints
                 ------------------------------------------
                 |  Lagrange Multiplier  or  Wald Index   |
                 ------------------------------------------
                 |  Probability  | Approx Change of Value |
                 ------------------------------------------

                           E1                    E2                    E3

     E1          0.000               111.175  [RO1]        168.678  [RO2]
                 1.000  0.000

     E2        111.175  [RO1]          0.000               168.678  [RO2]
                                       1.000  0.000

     E3        168.678  [RO2]        168.678  [RO2]          0.000
                                                             1.000  0.000

     E4        168.678  [RO2]        168.678  [RO2]         81.012  [RO3]


     E5        168.678  [RO2]        168.678  [RO2]         81.012  [RO3]



                                      E4                    E5

                E1        168.678  [RO2]        168.678  [RO2]


                E2        168.678  [RO2]        168.678  [RO2]


                E3         81.012  [RO3]         81.012  [RO3]


                E4          0.000                81.012  [RO3]
                            1.000  0.000

                E5         81.012  [RO3]          0.000
                                                  1.000  0.000

                     CALIS65: Special LISREL Application                    13
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

       Covariance Structure Analysis: Weighted Least-Squares Estimation

                      Univariate Lagrange Multiplier Test
                      For Releasing Equality Constraints
------------------------------------------------------------------------------
 Chi-Square    Prob          Change       Parameter          Equal to
------------------------------------------------------------------------------

    2.815832   0.0933  -0.0715 =  0.00838  [E3:E1] = [E3:E2] [E4:E1] [E4:E2]
                                                     [E5:E1] [E5:E2]
    4.758876   0.0291   0.0603 =  -0.0359  [E3:E2] = [E3:E1] [E4:E1] [E4:E2]
                                                     [E5:E1] [E5:E2]
    1.032967   0.3095  -0.0659 = -0.00155  [E4:E1] = [E3:E1] [E3:E2] [E4:E2]
                                                     [E5:E1] [E5:E2]
    1.302121   0.2538  -0.0692 = -0.00597  [E4:E2] = [E3:E1] [E3:E2] [E4:E1]
                                                     [E5:E1] [E5:E2]
    0.576782   0.4476  -0.0345 =  0.00441  [E5:E1] = [E3:E1] [E3:E2] [E4:E1]
                                                     [E4:E2] [E5:E2]
    3.235721   0.0720   0.0411 =  -0.0458  [E5:E2] = [E3:E1] [E3:E2] [E4:E1]
                                                     [E4:E2] [E5:E1]

    1.838465   0.1751   0.0517 =  -0.0244  [E4:E3] = [E5:E3] [E5:E4]
   11.914590 0.000557  -0.1608 =   0.0268  [E5:E3] = [E4:E3] [E5:E4]
    4.666367   0.0308   0.0550 =  -0.0637  [E5:E4] = [E4:E3] [E5:E3]

                     CALIS65: Special LISREL Application                    14
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

       OBS    _TYPE_    _NAME_    VAR1    VAR2    VAR3    VAR4    VAR5

        1     WEIGHT     VAR1       0       1       1       1       1
        2     WEIGHT     VAR2       1       0       1       1       1
        3     WEIGHT     VAR3       1       1       0       1       1
        4     WEIGHT     VAR4       1       1       1       0       1
        5     WEIGHT     VAR5       1       1       1       1       0

                     CALIS65: Special LISREL Application                    15
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

          Covariance Structure Analysis: Pattern and Initial Values

              COSAN Model Statement
         -------------------------------
              Matrix         Rows & Cols          Matrix Type

 TERM   1-----------------------------------------------------------
           1    PHI            5       5    SYMMETRIC

                      Initial Parameter Matrix PHI[5:5]
                               Symmetric Matrix

                COL1          COL2          COL3          COL4          COL5

  VAR1    1.00           .  [RHO1]     .  [RHO2]     .  [RHO2]     .  [RHO2]
  VAR2     .  [RHO1]    1.00           .  [RHO2]     .  [RHO2]     .  [RHO2]
  VAR3     .  [RHO2]     .  [RHO2]    1.00           .  [RHO3]     .  [RHO3]
  VAR4     .  [RHO2]     .  [RHO2]     .  [RHO3]    1.00           .  [RHO3]
  VAR5     .  [RHO2]     .  [RHO2]     .  [RHO3]     .  [RHO3]    1.00

                                Weight Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       0.0000       1.0000       1.0000       1.0000       1.0000
    VAR2       1.0000       0.0000       1.0000       1.0000       1.0000
    VAR3       1.0000       1.0000       0.0000       1.0000       1.0000
    VAR4       1.0000       1.0000       1.0000       0.0000       1.0000
    VAR5       1.0000       1.0000       1.0000       1.0000       0.0000
                        Determinant of Weight Matrix 0

                     CALIS65: Special LISREL Application                    16
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

 Covariance Structure Analysis: Diagonally Weighted Least-Squares Estimation

                   200 Observations       Model Terms          1
                     5 Variables          Model Matrices       1
                    15 Informations       Parameters           3

                 VARIABLE              Mean           Std Dev

                 VAR1                     0       1.000000000
                 VAR2                     0       1.000000000
                 VAR3                     0       1.000000000
                 VAR4                     0       1.000000000
                 VAR5                     0       1.000000000

                                 Correlations

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       1.0000       0.5264       0.4021       0.3910       0.4169
    VAR2       0.5264       1.0000       0.4819       0.4236       0.4889
    VAR3       0.4021       0.4819       1.0000       0.3997       0.2743
    VAR4       0.3910       0.4236       0.3997       1.0000       0.4417
    VAR5       0.4169       0.4889       0.2743       0.4417       1.0000
                      Determinant = 0.2681 (Ln = -1.316)

                         Vector of Initial Estimates

 RHO1          1    0.50000  Matrix Entry: PHI[2:1]
 RHO2          2    0.50000  Matrix Entry: PHI[3:1] PHI[3:2] PHI[4:1] PHI[4:2]
                                           PHI[5:1] PHI[5:2]
 RHO3          3    0.50000  Matrix Entry: PHI[4:3] PHI[5:3] PHI[5:4]

            Predetermined Elements of the Predicted Moment Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       1.0000        .            .            .            .
    VAR2        .           1.0000        .            .            .
    VAR3        .            .           1.0000        .            .
    VAR4        .            .            .           1.0000        .
    VAR5        .            .            .            .           1.0000
                        Sum of Squared Differences = 0

NOTE: The degrees of freedom are reduced by 5.

                     CALIS65: Special LISREL Application                    17
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

 Covariance Structure Analysis: Diagonally Weighted Least-Squares Estimation

                       Levenberg-Marquardt Optimization
                        Scaling Update of More (1978)
                       Number of Parameter Estimates 3
                    Number of Functions (Observations) 15

Optimization Start: Active Constraints= 0  Criterion= 0.100
Maximum Gradient Element= 0.396 Radius= 1.176

        Iter rest nfun act   optcrit  difcrit maxgrad  lambda     rho

           1    0    2   0    0.0238   0.0760 167E-18       0   2.000

Optimization Results: Iterations= 1 Function Calls= 3 Jacobian Calls= 2
Active Constraints= 0  Criterion= 0.023755689
Maximum Gradient Element= 1.66533E-16 Lambda= 0 Rho= 2 Radius= 0.5513

NOTE:  ABSGCONV convergence criterion satisfied.

                     CALIS65: Special LISREL Application                    18
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

 Covariance Structure Analysis: Diagonally Weighted Least-Squares Estimation

                            Predicted Model Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       1.0000       0.5264       0.4341       0.4341       0.4341
    VAR2       0.5264       1.0000       0.4341       0.4341       0.4341
    VAR3       0.4341       0.4341       1.0000       0.3719       0.3719
    VAR4       0.4341       0.4341       0.3719       1.0000       0.3719
    VAR5       0.4341       0.4341       0.3719       0.3719       1.0000
                      Determinant = 0.2861 (Ln = -1.251)

                     CALIS65: Special LISREL Application                    19
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

 Covariance Structure Analysis: Diagonally Weighted Least-Squares Estimation

         Fit criterion . . . . . . . . . . . . . . . . . .     0.0238
         Goodness of Fit Index (GFI) . . . . . . . . . . .     0.9871
         GFI Adjusted for Degrees of Freedom (AGFI). . . .     0.9724
         Root Mean Square Residual (RMR) . . . . . . . . .     0.0398
         Parsimonious GFI (Mulaik, 1989) . . . . . . . . .     0.6910

                               Residual Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1      0.00000      0.00000      -.03194      -.04311      -.01715
    VAR2      0.00000      0.00000      0.04779      -.01044      0.05486
    VAR3      -.03194      0.04779      0.00000      0.02781      -.09763
    VAR4      -.04311      -.01044      0.02781      0.00000      0.06982
    VAR5      -.01715      0.05486      -.09763      0.06982      0.00000
                     Average Absolute Residual = 0.0267
               Average Off-diagonal Absolute Residual = 0.04006

                      Rank Order of 7 Largest Residuals

  VAR5,VAR3  VAR5,VAR4  VAR5,VAR2  VAR3,VAR2  VAR4,VAR1  VAR3,VAR1  VAR4,VAR3
   -0.09763    0.06982    0.05486    0.04779   -0.04311   -0.03194    0.02781

                    Variance Standardized Residual Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1      0.00000      0.00000      -.03194      -.04311      -.01715
    VAR2      0.00000      0.00000      0.04779      -.01044      0.05486
    VAR3      -.03194      0.04779      0.00000      0.02781      -.09763
    VAR4      -.04311      -.01044      0.02781      0.00000      0.06982
    VAR5      -.01715      0.05486      -.09763      0.06982      0.00000
                   Average Standardized Residual = 0.0267
             Average Off-diagonal Standardized Residual = 0.04006

           Rank Order of 7 Largest Variance Standardized Residuals

  VAR5,VAR3  VAR5,VAR4  VAR5,VAR2  VAR3,VAR2  VAR4,VAR1  VAR3,VAR1  VAR4,VAR3
   -0.09763    0.06982    0.05486    0.04779   -0.04311   -0.03194    0.02781

                     CALIS65: Special LISREL Application                    20
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

 Covariance Structure Analysis: Diagonally Weighted Least-Squares Estimation

               Distribution of Variance Standardized Residuals
                       (Each * represents 1 residuals)

                   -0.11163 -   -0.08373  1   6.67% | *
                   -0.08373 -   -0.05582  0   0.00% |
                   -0.05582 -   -0.02791  2  13.33% | **
                   -0.02791 -          0  2  13.33% | **
                          0 -    0.02791  7  46.67% | *******
                    0.02791 -    0.05582  2  13.33% | **
                    0.05582 -    0.08373  1   6.67% | *

                     Estimated Parameter Matrix PHI[5:5]
                               Symmetric Matrix

                           COL1                COL2                COL3

       VAR1        1.0000              0.5264[RHO1]        0.4341[RHO2]
       VAR2        0.5264[RHO1]        1.0000              0.4341[RHO2]
       VAR3        0.4341[RHO2]        0.4341[RHO2]        1.0000
       VAR4        0.4341[RHO2]        0.4341[RHO2]        0.3719[RHO3]
       VAR5        0.4341[RHO2]        0.4341[RHO2]        0.3719[RHO3]


                                     COL4                COL5

                 VAR1        0.4341[RHO2]        0.4341[RHO2]
                 VAR2        0.4341[RHO2]        0.4341[RHO2]
                 VAR3        0.3719[RHO3]        0.3719[RHO3]
                 VAR4        1.0000              0.3719[RHO3]
                 VAR5        0.3719[RHO3]        1.0000

                     CALIS65: Special LISREL Application                    21
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

          Covariance Structure Analysis: Pattern and Initial Values

              COSAN Model Statement
         -------------------------------
              Matrix         Rows & Cols          Matrix Type

 TERM   1-----------------------------------------------------------
           1    PHI            5       5    SYMMETRIC

                      Initial Parameter Matrix PHI[5:5]
                               Symmetric Matrix

                COL1          COL2          COL3          COL4          COL5

  VAR1    1.00           .  [RHO1]     .  [RHO2]     .  [RHO2]     .  [RHO2]
  VAR2     .  [RHO1]    1.00           .  [RHO2]     .  [RHO2]     .  [RHO2]
  VAR3     .  [RHO2]     .  [RHO2]    1.00           .  [RHO3]     .  [RHO3]
  VAR4     .  [RHO2]     .  [RHO2]     .  [RHO3]    1.00           .  [RHO3]
  VAR5     .  [RHO2]     .  [RHO2]     .  [RHO3]     .  [RHO3]    1.00

                                Weight Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       0.0010       1.0000       1.0000       1.0000       1.0000
    VAR2       1.0000       0.0010       1.0000       1.0000       1.0000
    VAR3       1.0000       1.0000       0.0010       1.0000       1.0000
    VAR4       1.0000       1.0000       1.0000       0.0010       1.0000
    VAR5       1.0000       1.0000       1.0000       1.0000       0.0010
                      Determinant of Weight Matrix 1E-15

                     CALIS65: Special LISREL Application                    22
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

 Covariance Structure Analysis: Diagonally Weighted Least-Squares Estimation

                   200 Observations       Model Terms          1
                     5 Variables          Model Matrices       1
                    15 Informations       Parameters           3

                 VARIABLE              Mean           Std Dev

                 VAR1                     0       1.000000000
                 VAR2                     0       1.000000000
                 VAR3                     0       1.000000000
                 VAR4                     0       1.000000000
                 VAR5                     0       1.000000000

                                 Correlations

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       1.0000       0.5264       0.4021       0.3910       0.4169
    VAR2       0.5264       1.0000       0.4819       0.4236       0.4889
    VAR3       0.4021       0.4819       1.0000       0.3997       0.2743
    VAR4       0.3910       0.4236       0.3997       1.0000       0.4417
    VAR5       0.4169       0.4889       0.2743       0.4417       1.0000
                      Determinant = 0.2681 (Ln = -1.316)

                         Vector of Initial Estimates

 RHO1          1    0.50000  Matrix Entry: PHI[2:1]
 RHO2          2    0.50000  Matrix Entry: PHI[3:1] PHI[3:2] PHI[4:1] PHI[4:2]
                                           PHI[5:1] PHI[5:2]
 RHO3          3    0.50000  Matrix Entry: PHI[4:3] PHI[5:3] PHI[5:4]

            Predetermined Elements of the Predicted Moment Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       1.0000        .            .            .            .
    VAR2        .           1.0000        .            .            .
    VAR3        .            .           1.0000        .            .
    VAR4        .            .            .           1.0000        .
    VAR5        .            .            .            .           1.0000
                        Sum of Squared Differences = 0

NOTE: The degrees of freedom are reduced by 5.

                     CALIS65: Special LISREL Application                    23
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

 Covariance Structure Analysis: Diagonally Weighted Least-Squares Estimation

                       Levenberg-Marquardt Optimization
                        Scaling Update of More (1978)
                       Number of Parameter Estimates 3
                    Number of Functions (Observations) 15

Optimization Start: Active Constraints= 0  Criterion= 0.100
Maximum Gradient Element= 0.396 Radius= 1.176

        Iter rest nfun act   optcrit  difcrit maxgrad  lambda     rho

           1    0    2   0    0.0238   0.0760 167E-18       0   2.000

Optimization Results: Iterations= 1 Function Calls= 3 Jacobian Calls= 2
Active Constraints= 0  Criterion= 0.023755689
Maximum Gradient Element= 1.66533E-16 Lambda= 0 Rho= 2 Radius= 0.5513

NOTE:  ABSGCONV convergence criterion satisfied.

                     CALIS65: Special LISREL Application                    24
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

 Covariance Structure Analysis: Diagonally Weighted Least-Squares Estimation

                            Predicted Model Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1       1.0000       0.5264       0.4341       0.4341       0.4341
    VAR2       0.5264       1.0000       0.4341       0.4341       0.4341
    VAR3       0.4341       0.4341       1.0000       0.3719       0.3719
    VAR4       0.4341       0.4341       0.3719       1.0000       0.3719
    VAR5       0.4341       0.4341       0.3719       0.3719       1.0000
                      Determinant = 0.2861 (Ln = -1.251)

                     CALIS65: Special LISREL Application                    25
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

 Covariance Structure Analysis: Diagonally Weighted Least-Squares Estimation

         Fit criterion . . . . . . . . . . . . . . . . . .     0.0238
         Goodness of Fit Index (GFI) . . . . . . . . . . .     1.0000
         GFI Adjusted for Degrees of Freedom (AGFI). . . .     1.0000
         Root Mean Square Residual (RMR) . . . . . . . . .     0.0398
         Parsimonious GFI (Mulaik, 1989) . . . . . . . . .     0.7000

                               Residual Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1      0.00000      0.00000      -.03194      -.04311      -.01715
    VAR2      0.00000      0.00000      0.04779      -.01044      0.05486
    VAR3      -.03194      0.04779      0.00000      0.02781      -.09763
    VAR4      -.04311      -.01044      0.02781      0.00000      0.06982
    VAR5      -.01715      0.05486      -.09763      0.06982      0.00000
                     Average Absolute Residual = 0.0267
               Average Off-diagonal Absolute Residual = 0.04006

                      Rank Order of 7 Largest Residuals

  VAR5,VAR3  VAR5,VAR4  VAR5,VAR2  VAR3,VAR2  VAR4,VAR1  VAR3,VAR1  VAR4,VAR3
   -0.09763    0.06982    0.05486    0.04779   -0.04311   -0.03194    0.02781

                    Variance Standardized Residual Matrix

                 VAR1         VAR2         VAR3         VAR4         VAR5

    VAR1      0.00000      0.00000      -.03194      -.04311      -.01715
    VAR2      0.00000      0.00000      0.04779      -.01044      0.05486
    VAR3      -.03194      0.04779      0.00000      0.02781      -.09763
    VAR4      -.04311      -.01044      0.02781      0.00000      0.06982
    VAR5      -.01715      0.05486      -.09763      0.06982      0.00000
                   Average Standardized Residual = 0.0267
             Average Off-diagonal Standardized Residual = 0.04006

           Rank Order of 7 Largest Variance Standardized Residuals

  VAR5,VAR3  VAR5,VAR4  VAR5,VAR2  VAR3,VAR2  VAR4,VAR1  VAR3,VAR1  VAR4,VAR3
   -0.09763    0.06982    0.05486    0.04779   -0.04311   -0.03194    0.02781

                     CALIS65: Special LISREL Application                    26
                     Example 7.5, LISREL 7, 1988, p. 208
             Estimating PHI Matrix, Results see LISREL 7, p. 209

 Covariance Structure Analysis: Diagonally Weighted Least-Squares Estimation

               Distribution of Variance Standardized Residuals
                       (Each * represents 1 residuals)

                   -0.11163 -   -0.08373  1   6.67% | *
                   -0.08373 -   -0.05582  0   0.00% |
                   -0.05582 -   -0.02791  2  13.33% | **
                   -0.02791 -          0  2  13.33% | **
                          0 -    0.02791  7  46.67% | *******
                    0.02791 -    0.05582  2  13.33% | **
                    0.05582 -    0.08373  1   6.67% | *

                     Estimated Parameter Matrix PHI[5:5]
                               Symmetric Matrix

                           COL1                COL2                COL3

       VAR1        1.0000              0.5264[RHO1]        0.4341[RHO2]
       VAR2        0.5264[RHO1]        1.0000              0.4341[RHO2]
       VAR3        0.4341[RHO2]        0.4341[RHO2]        1.0000
       VAR4        0.4341[RHO2]        0.4341[RHO2]        0.3719[RHO3]
       VAR5        0.4341[RHO2]        0.4341[RHO2]        0.3719[RHO3]


                                     COL4                COL5

                 VAR1        0.4341[RHO2]        0.4341[RHO2]
                 VAR2        0.4341[RHO2]        0.4341[RHO2]
                 VAR3        0.3719[RHO3]        0.3719[RHO3]
                 VAR4        1.0000              0.3719[RHO3]
                 VAR5        0.3719[RHO3]        1.0000