5-3.9 Generalizing the adjustment algorithms.

As with presence dependence we may use subscripts for each combination so as to also refer directly to the length (n) of the dependency chain. So what we are saying is that we can use n to refer to the combination [ 1, 2, . . . , n ]. The adjusted reliability viz., coincidence for combination k is ark, viz., ack and there are k fields agreeing in combinations of fields in dependency chains of arbitrary length (n). We say that k = i, except where k = i = 0 when ro = 1, viz., co = 1, and where k = i = n+1 when rn+1 = 0, viz., cn+1 = 0.

ark = ri – ri+1(5.3)
ack = ci – ci+1(5.4)
FIELD
Presence		 Reliability &
Coincidence		 W E I G H T S   F O R   C O M B I N A T I O N S
(+ = agreement  – = disagreement   0 = missing)
 p   r   c  + + + – + 0 – + – – – 0 0 + 0 – 0 0
Principal's
Given Name
Code 0.9679		 0.9617
ar1 =
0.1598		 0.0250
ac1 =
0.0084		 aw1 = +5.27 aw1 = +5.27
aw3 = +4.17		 aw1 =
+5.27		 dw1 =
–7.25		 dw1 =
–7.25		 dw1 =
–7.25		 bw1 =
0.00		 bw1 =
0.00		 bw1 =
0.00
Principal's
Given Name
Spelling
0.9696		 0.8019
ar2 =
0.8402		 0.0166
ac2 =
0.9916		 aw2 = +5.59 dw2 = –2.31
dw3 = +0.24		 bw2 =
0.00		 aw2 =
+5.59		 dw2 =
–2.31		 bw2 =
0.00		 aw2 =
+5.59		 dw2 =
–2.31		 bw2 =
0.00
Given Name
Code depends
on Spelling		 0.8019 0.0166 cw =
aw2 =
+5.59 		cw3 =
+3.93 		does
not
occur		 does
not
occur		 cw =
dw2 =
–2.31		 does
not
occur		 does
not
occur		 does
not
occur		 does
not
occur

Table 6 — Weighting Constructively Dependent Fields

Table 6 shows the effect on the record comparison weight when two fields are constructively dependent. Two comparisons are possible where only the spelling is important. In these cases using the adjusted reliability and coincidence (shown to left) is equivalent to considering only the spelling. In one case adjusted values are indispensable. The coincidence of spellings agreeing, when the code agrees is a very high value, i.e., this situation isn't much of a coincidence, particularly when the code partitions the spelling so finely. These adjustment values are more important when calculating the outcome probabilities.

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