Example 13: Paired comparisons as the basis for measurement |
Paired comparisons can be modeled directly with the Facets computer program. For Winsteps a dummy facet of "occasion" or "pairing" must be introduced. On each occasion (in this example, each column), there is a winner '1', a loser '0', or a draw 'D' recorded for the two players. The data can be set up with the paired objects as rows and the pairings as columns, or the paired objects as columns or the pairings as rows. Analytically it makes no differences, so do it the way that is easier for your.
In this example, the paired objects are the rows, and the pairings are the columns. In column 1 of the response data in this example, Browne (1) defeated Mariotti (0). In column 2, Browne (D) drew with Tatai (D). Specifying PAIRED=YES adjusts the measures for the statistical bias introduced by this stratagem. Each player receives a measure and fit statistics. Occasion measures are the average of the two players participating. Misfitting occasions are unexpected outcomes. Point-biserial correlations have little meaning. Check the occasion summary statistics in Table 3.1 to verify that all occasions have the same raw score.
; This common control file is EXAM13.TXT
TITLE = 'Chess Matches at the Venice Tournament, 1971'
Name1 = 1 ; Player's name
Item1 = 11 ; First match results
PERSON = PLAYER
ITEM = MATCH ; Example of paired comparison
CODES = 0D1 ; 0 = loss, D = draw (non-numeric), 1 = win
; if you wish to just consider won-loss, and ignore the draws, omit the following line:
NEWSCORE = 012 ; 0 = loss, 1 = draw, 2 = win
CLFILE=*
0 Loss
D Draw
1 Win
*
NI = 66 ; 66 matches (columns) in total
PAIRED = YES ; specify the paired comparison adjustment
INUMBER = YES ; number the matches in the Output
&END
Browne 1D 0 1 1 1 1 D D 1 1
Mariotti 0 1 D 0 1 1 1 D 1 D 1
Tatai D0 0 1 D D 1 1 1 1 D
Hort 1D1 D D 1 D D D 1 0
Kavalek 010D D D 1 D 1 1 D
Damjanovic 00DDD D D D 1 D 1
Gligoric 00D0DD D 1 1 1 0
Radulov 000D0DD D 1 D 1
Bobotsov DD0DDD0D 0 0 1
Cosulich D00D00001 1 1
Westerinen 0D000D0D10 1
Zichichi 00D1D010000
Part of the output is:
PLAYER STATISTICS: MEASURE ORDER
+---------------------------------------------------------------------+
|ENTRY RAW | INFIT | OUTFIT | |
|NUMBR SCORE COUNT MEASURE ERROR|MNSQ ZSTD|MNSQ ZSTD| PLAYER |
|-----------------------------------+----------+----------+-----------|
| 1 17 11 1.09 .35|1.10 .2|1.02 .1| Browne |
| 2 15 11 .68 .32|1.02 .0| .96 -.1| Mariotti |
| 3 14 11 .50 .31| .86 -.4| .83 -.5| Tatai |
| 4 14 11 .50 .31|1.34 .9|1.54 1.3| Hort |
| 5 13 11 .33 .31| .81 -.6| .80 -.6| Kavalek |
| 6 11 11 .00 .30| .35 -2.8| .37 -2.6| Damjanovic|
| 7 10 11 -.17 .30| .90 -.3| .91 -.3| Gligoric |
| 8 9 11 -.34 .31| .52 -1.8| .52 -1.7| Radulov |
| 9 8 11 -.51 .31|1.00 .0|1.00 .0| Bobotsov |
| 10 8 11 -.51 .31|1.18 .5|1.15 .4| Cosulich |
| 11 7 11 -.69 .32| .95 -.1| .89 -.3| Westerinen|
| 12 6 11 -.88 .33|1.86 1.8|1.90 1.7| Zichichi |
|-----------------------------------+----------+----------+-----------|
| MEAN 11. 11. .00 .32| .99 -.2| .99 -.2| |
+---------------------------------------------------------------------+
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