Table 5 Multivariate Logistic model classifying bad clusters from good
From: An efficient record linkage scheme using graphical analysis for identifier error detection
| Â | Â | Â | Model: Any Females | Model: No females | ||
|---|---|---|---|---|---|---|
Parameter | Example inputs | Distance function | Coefficient | p | Parameter | Example inputs |
constant |  |  | -3.33 | <1 × 10-16 | constant |  |
Date of birth, day | 02, 24 | Levensthein | 0.25 | 5 × 10-4 | Date of birth, day | 02, 24 |
Date of birth, month | 01, 11 | Levensthein | 0.43 | 1 × 10-4 | Date of birth, month | 01, 11 |
Date of birth, year | 1969, 2007 | Levensthein | 5.12 | <1 × 10-16 | Date of birth, year | 1969, 2007 |
Forename | John, Chris | Jaro-Winkler | 2.45 | <1 × 10-16 | Forename | John, Chris |
Hospital Number | 110111 or 223456 | Jaro-Winkler | -0.56 | <1 × 10-16 | Hospital Number | 110111 or 223456 |
Surname | Smith, Jones | Jaro-Winkler | not present | - | Surname | Smith, Jones |
Sex | M, F | Levensthein | 0.80 | <1 × 10-16 | Sex | M, F |