diyar

Overview

Record linkage and deduplication of individual-level data, such as repeated spells in hospital, or recurrent cases of infection is a common task in epidemiological analysis and other fields of research.

The diyar package aims to provide a simple and flexible implementation of multistage deterministic record linkage and episode grouping.

Installation

# Install the latest CRAN release 
install.packages("diyar")

# Or, install the development version from GitHub
install.packages("devtools")
devtools::install_github("OlisaNsonwu/diyar")

Cheat sheet

Usage

There are two main aspects of the diyar package; multistage data linkage grouping (links()) and episode tracking (episodes()). number_line objects are used in both.

• number_line() - creates a range of real numbers on a number line.
  • They can be manipulated - reverse_number_line, shift_number_line, expand_number_line, number_line_sequence, invert_number_line, compress_number_line, union_number_lines, subtract_number_lines, intersect_number_lines.
  • Logical tests for overlap - overlaps, overlap, exact, reverse, chain, across, aligns_start, aligns_end, inbetween.

library(diyar)

l <- as.Date("01/04/2019", "%d/%m/%Y"); r <- as.Date("30/04/2019", "%d/%m/%Y")
nl <- number_line(l, r)
nl
#> [1] "2019-04-01 -> 2019-04-30"
reverse_number_line(nl)
#> [1] "2019-04-30 <- 2019-04-01"
expand_number_line(nl, -2)
#> [1] "2019-04-03 -> 2019-04-28"

• episodes() - tracks temporal episodes.

data(infections);
db <- infections[c("date")]
# Dates
db$date
#>  [1] "2018-04-01" "2018-04-07" "2018-04-13" "2018-04-19" "2018-04-25"
#>  [6] "2018-05-01" "2018-05-07" "2018-05-13" "2018-05-19" "2018-05-25"
#> [11] "2018-05-31"

# Fixed episodes
episodes(date = db$date, 
         case_length = 15, 
         display = "none", 
         group_stats = TRUE)
#> Episode tracking completed in < 0.01 secs!
#>  [1] "E.01 2018-04-01 -> 2018-04-13 (C)" "E.01 2018-04-01 -> 2018-04-13 (D)"
#>  [3] "E.01 2018-04-01 -> 2018-04-13 (D)" "E.04 2018-04-19 -> 2018-05-01 (C)"
#>  [5] "E.04 2018-04-19 -> 2018-05-01 (D)" "E.04 2018-04-19 -> 2018-05-01 (D)"
#>  [7] "E.07 2018-05-07 -> 2018-05-19 (C)" "E.07 2018-05-07 -> 2018-05-19 (D)"
#>  [9] "E.07 2018-05-07 -> 2018-05-19 (D)" "E.10 2018-05-25 -> 2018-05-31 (C)"
#> [11] "E.10 2018-05-25 -> 2018-05-31 (D)"

# Rolling episodes
episodes(date = db$date, 
         case_length = 15, 
         recurrence_length = 40, 
         display = "none",
         episode_type = "rolling", 
         group_stats = TRUE)
#> Episode tracking completed in < 0.01 secs!
#>  [1] "E.1 2018-04-01 -> 2018-05-31 (C)" "E.1 2018-04-01 -> 2018-05-31 (D)"
#>  [3] "E.1 2018-04-01 -> 2018-05-31 (D)" "E.1 2018-04-01 -> 2018-05-31 (R)"
#>  [5] "E.1 2018-04-01 -> 2018-05-31 (D)" "E.1 2018-04-01 -> 2018-05-31 (D)"
#>  [7] "E.1 2018-04-01 -> 2018-05-31 (D)" "E.1 2018-04-01 -> 2018-05-31 (D)"
#>  [9] "E.1 2018-04-01 -> 2018-05-31 (D)" "E.1 2018-04-01 -> 2018-05-31 (R)"
#> [11] "E.1 2018-04-01 -> 2018-05-31 (D)"

• links() - multistage deterministic linkage with missing data.

# Two-stage exact matches
data(staff_records);

staff_records$pids_a <- links(criteria = list(staff_records$forename, 
                                              staff_records$surname),
                              data_source = staff_records$sex, 
                              display = "none")
#> Data linkage completed in < 0.01 secs!
staff_records
#>   r_id forename  surname sex    dataset        pids_a
#> 1    1    James    Green   M Staff list P.1 (CRI 002)
#> 2    2     <NA> Anderson   M Staff list P.2 (CRI 002)
#> 3    3    Jamey    Green   M  Pay slips P.1 (CRI 002)
#> 4    4              <NA>   F  Pay slips P.4 (No Hits)
#> 5    5  Derrick Anderson   M Staff list P.2 (CRI 002)
#> 6    6  Darrack Anderson   M  Pay slips P.2 (CRI 002)
#> 7    7 Christie    Green   F Staff list P.1 (CRI 002)

# Single-stage user-defined logical tests
# Matching `sex` and + 20-year age gaps
age <- c(30, 28, 40, 25, 25, 29, 27)
sex <- c("M", "M", "M", "F", "M", "M", "F")
f1 <- function(x, y) (y - x) %in% 0:20
links(criteria = sex,
      sub_criteria = list(cr1 = sub_criteria(age, funcs = f1)),
      display = "none")
#> Data linkage completed in < 0.01 secs!
#> [1] "P.3 (CRI 001)" "P.3 (CRI 001)" "P.3 (CRI 001)" "P.7 (CRI 001)"
#> [5] "P.3 (CRI 001)" "P.3 (CRI 001)" "P.7 (CRI 001)"

# + 20-year age gaps only
links(criteria = "place_holder",
      sub_criteria = list(cr1 = sub_criteria(age, funcs = f1)),
      display = "none")
#> Data linkage completed in < 0.01 secs!
#> [1] "P.3 (CRI 001)" "P.3 (CRI 001)" "P.3 (CRI 001)" "P.3 (CRI 001)"
#> [5] "P.3 (CRI 001)" "P.3 (CRI 001)" "P.3 (CRI 001)"

Find out more here!

Bugs and issues

Please report any bug or issues with using this package here.