sub_criteria: Match criteria
In diyar: Record Linkage and Epidemiological Case Definitions in 'R'

sub_criteria

R Documentation

Match criteria

Description

Match criteria for record linkage with links and episodes

Usage

sub_criteria(
  ...,
  match_funcs = c(exact = diyar::exact_match),
  equal_funcs = c(exact = diyar::exact_match),
  operator = "or"
)

attrs(..., .obj = NULL)

eval_sub_criteria(x, ...)

## S3 method for class 'sub_criteria'
print(x, ...)

## S3 method for class 'sub_criteria'
format(x, show_levels = FALSE, ...)

## S3 method for class 'sub_criteria'
eval_sub_criteria(
  x,
  x_pos = seq_len(max(attr_eval(x))),
  y_pos = rep(1L, length(x_pos)),
  check_duplicates = TRUE,
  depth = 0,
  ...
)

Arguments

`...`	`[atomic]` Attributes passed to or `eval_sub_criteria()` or `eval_sub_criteria()` Arguments passed to methods for `eval_sub_criteria()`
`match_funcs`	`[function]`. User defined logical test for matches.
`equal_funcs`	`[function]`. User defined logical test for identical record sets (all attributes of the same record).
`operator`	`[character]`. Options are `"and"` or `"or"`.
`.obj`	`[data.frame\|list]`. Attributes.
`x`	`[sub_criteria]`. Attributes.
`show_levels`	`[logical]`. If `TRUE`, show recursive depth for each logic statement of the match criteria.
`x_pos`	`[integer]`. Index of one half of a record pair.
`y_pos`	`[integer]`. Index of one half of a record pair.
`check_duplicates`	`[logical]`. If `FALSE`, does not check duplicate values. The result of the initial check will be recycled.
`depth`	`[integer]`. First order of recursion.

Details

sub_criteria() - Create a match criteria as a sub_criteria object. A sub_criteria object contains attributes to be compared, logical tests for the comparisons (see predefined_tests for examples) and another set of logical tests to determine identical records.

attrs() - Create a d_attribute object - a collection of atomic objects that can be passed to sub_criteria() as a single attribute.

eval_sub_criteria() - Evaluates a sub_criteria object.

At each iteration of links or episodes, record-pairs are created from each attribute of a sub_criteria object. eval_sub_criteria() evaluates each record-pair using the match_funcs and equal_funcs functions of a sub_criteria object. See predefined_tests for examples of match_funcs and equal_funcs.

User-defined functions are also permitted as match_funcs and equal_funcs. Such functions must meet three requirements:

It must be able to compare the attributes.
It must have two arguments named `x` and `y`, where `y` is the value for one observation being compared against all other observations (`x`).
It must return a logical object i.e. TRUE or FALSE.

attrs() is useful when the match criteria requires an interaction between the multiple attributes. For example, attribute 1 + attribute 2 > attribute 3.

Every attribute, including those in attrs(), must have the same length or a length of 1.

Value

sub_criteria

Examples

# Attributes
attr_1 <- c(30, 28, 40, 25, 25, 29, 27)
attr_2 <- c("M", "F", "U", "M", "F", "U", "M")

# A match criteria
## Example 1 - A maximum difference of 10 in attribute 1
s_cri1 <- sub_criteria(attr_1, match_funcs = range_match)
s_cri1

# Evaluate the match criteria
## Compare the first element of 'attr_1' against all other elements
eval_sub_criteria(s_cri1)
## Compare the second element of 'attr_1' against all other elements
x_pos_val <- seq_len(max(attr_eval(s_cri1)))
eval_sub_criteria(s_cri1,
                  x_pos = x_pos_val,
                  y_pos = rep(2, length(x_pos_val)))

## Example 2 - `s_cri1` AND an exact match on attribute 2
s_cri2 <- sub_criteria(
  s_cri1,
  sub_criteria(attr_2, match_funcs = exact_match),
  operator = "and")
s_cri2

## Example 3 - `s_cri1` OR an exact match on attribute 2
s_cri3 <- sub_criteria(
  s_cri1,
  sub_criteria(attr_2, match_funcs = exact_match),
  operator = "or")
s_cri3

# Evaluate the match criteria
eval_sub_criteria(s_cri2)
eval_sub_criteria(s_cri3)

# Alternatively, using `attr()`
AND_func <- function(x, y) range_match(x$a1, y$a1) & x$a2 == y$a2
OR_func <- function(x, y) range_match(x$a1, y$a1) | x$a2 == y$a2

## Create a match criteria
s_cri2b <- sub_criteria(attrs(.obj = list(a1 = attr_1, a2 = attr_2)),
                        match_funcs = AND_func)
s_cri3b <- sub_criteria(attrs(.obj = list(a1 = attr_1, a2 = attr_2)),
                        match_funcs = OR_func)

# Evaluate the match criteria
eval_sub_criteria(s_cri2b)
eval_sub_criteria(s_cri3b)

diyar documentation built on Nov. 13, 2023, 1:08 a.m.