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Pairwise Analysis of Australian Football League            Fri Apr  5 10:21 2024
SUMMARY OF THE ESTIMATION
==============================================================Version: 5.39.2===

DATA SPECIFICATIONS

The Data File: afl.dat
The format:  team1 1-13 team2 14-26 responses 38
Number of comparisons: 2124


MODEL SPECIFICATIONS

Assumed population distribution was: Gaussian
Location constraint was: Not applicable
Scale constraint was: Not applicable
Case weights not applicable
The regression model:
Grouping Variables:
The item model: team1-team2
Slopes are fixed
Total number of estimated parameters: 15
Random number generation seed:    2.00000
Number of nodes used when drawing PVs: 2000
Number of plausible values to draw: 5
Maximum number of iterations without a deviance improvement: 100
Maximum number of Newton steps for each parameter in M-step: 10
Value for obtaining finite MLEs for zero/perfects:    0.30000


ESTIMATION SPECIFICATIONS AND FIT

Estimation method was: Maximum Likelihood for Pairwise Comparisons
Final Deviance: Not applicable
The number of iterations: 4
Termination criteria:  Max iterations=1000,Parameter Change= 0.00010
                       Deviance Change= 0.00010
Iterations terminated because the convergence criteria were reached
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Pairwise Analysis of Australian Football League            Fri Apr  5 10:21 2024
PAIRIWSE MODEL
==============================================================Version: 5.39.2===
Parameter Estimates
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   VARIABLES                                  UNWEIGHTED FIT             WEIGHTED FIT
                                          -----------------------   ----------------------
                    ESTIMATE   ERROR     MNSQ       CI        T    MNSQ       CI        T
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Adelaide            0.16434   0.12338    0.99 ( 0.83, 1.17) -0.1   0.99 ( 0.96, 1.04) -0.6
Brisbane            0.36658   0.12391    1.02 ( 0.83, 1.17)  0.3   1.02 ( 0.95, 1.05)  0.8
Carlton            -0.40261   0.12706    1.00 ( 0.83, 1.17) -0.0   1.00 ( 0.94, 1.06) -0.1
Collingwood        -0.01258   0.12327    1.02 ( 0.83, 1.17)  0.2   1.02 ( 0.97, 1.03)  1.0
Essendon            0.17664   0.12395    0.99 ( 0.83, 1.17) -0.1   0.99 ( 0.96, 1.04) -0.7
Fremantle          -0.33520   0.12774    1.00 ( 0.83, 1.17) -0.0   1.00 ( 0.95, 1.05) -0.2
Geelong             0.40631   0.12581    1.00 ( 0.83, 1.17)  0.0   1.00 ( 0.94, 1.06)  0.1
Hawthorn           -0.05592   0.12451    0.98 ( 0.83, 1.17) -0.2   0.98 ( 0.97, 1.03) -1.2
Melbourne          -0.35280   0.12670    1.02 ( 0.83, 1.17)  0.2   1.02 ( 0.95, 1.05)  0.6
Nth Melbourne       0.08000   0.12401    1.00 ( 0.83, 1.17)  0.0   1.00 ( 0.97, 1.03)  0.1
Port Adelaide       0.26925   0.12383    1.00 ( 0.83, 1.17)  0.0   1.00 ( 0.96, 1.04) -0.0
Richmond           -0.47970   0.12972    1.00 ( 0.83, 1.17)  0.0   1.00 ( 0.93, 1.07) -0.0
St Kilda            0.00922   0.12399    0.98 ( 0.83, 1.17) -0.2   0.98 ( 0.97, 1.03) -1.2
Sydney              0.18382   0.12354    0.98 ( 0.83, 1.17) -0.2   0.98 ( 0.96, 1.04) -1.0
West Coast         -0.01327   0.12348    1.02 ( 0.83, 1.17)  0.3   1.02 ( 0.97, 1.03)  1.3
Wstn Bulldogs      -0.00408   0.12420    1.02 ( 0.83, 1.17)  0.2   1.02 ( 0.97, 1.03)  1.0
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An asterisk next to a parameter estimate indicates that it is constrained
A tilde next to a parameter estimate indicates that it is part of a random set
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