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diyar

CRAN version CRAN RStudio mirror downloads Coverage status Travis build status

Installation

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

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

Overview

diyar is an R package for linking records with shared characteristics. The linked records represent an entity, which depending on the context of the analysis can be unique patients, infection episodes, overlapping periods of care, clusters or other occurrences as defined by a case definition. This makes it useful in ordinarily complex analyses such as record linkage,
contact or network analyses e.t.c.

The main functions are links(), episodes() and partitions(). They are flexible in regards to how they compare records, as well as what are considered matches. Their functionality can sometimes overlap however, each is better suited to particular use cases:

Key features;

library(diyar)
data(missing_staff_id)
dfr_stages <- missing_staff_id[c("age", "hair_colour", "branch_office")]
priority_order_1 <- c("hair_colour", "branch_office")
priority_order_2 <- c("branch_office", "hair_colour")

dfr_stages$id.1 <- links(criteria = as.list(dfr_stages[priority_order_1]))
dfr_stages$id.2 <- links(criteria = as.list(dfr_stages[priority_order_2]))
sub.cri.1 <- sub_criteria(
  hair.color = dfr_stages$hair_colour,
  age = dfr_stages$age,
  match_funcs = c(
    "exact" = exact_match,
    "age.range" = range_match)
)
last_word_wf <- function(x) tolower(gsub("^.* ", "", x))
last_word_cmp <- function(x, y) last_word_wf(x) == last_word_wf(y)
not_equal <- function(x, y) x != y
sub.cri.2 <- sub_criteria(
  dfr_stages$branch_office, 
  dfr_stages$age,
  match_funcs = c(
    "last.word" = last_word_cmp,
    "not.equal" = not_equal)
)
sub.cri.3 <- sub_criteria(sub.cri.1, sub.cri.2, operator = "and")
sub.cri.1
#> {
#> exact(hair.color) OR age.range(age)
#> }
sub.cri.2
#> {
#> last.word(Republic of Ghana,France,NA ...) OR not.equal(30,30,30 ...)
#> }
sub.cri.3
#> {
#>   {
#>   exact(hair.color) OR age.range(age)
#>   } AND 
#>   {
#>   last.word(Republic of Ghana,France,NA ...) OR not.equal(30,30,30 ...)
#>   }
#> }
dfr_stages$id.3 <- links(
  criteria = "place_holder",
  sub_criteria = list("cr1" = sub.cri.3)
)
dfr_stages
#>   age hair_colour     branch_office          id.1          id.2          id.3
#> 1  30       Brown Republic of Ghana P.1 (CRI 001) P.1 (CRI 001) P.1 (CRI 001)
#> 2  30        Teal            France P.4 (CRI 003) P.2 (CRI 001) P.2 (CRI 001)
#> 3  30        <NA>              <NA> P.3 (No hits) P.3 (No hits) P.3 (No hits)
#> 4  30       Green              <NA> P.4 (CRI 001) P.2 (CRI 003) P.4 (No hits)
#> 5  30       Green            France P.4 (CRI 001) P.2 (CRI 001) P.2 (CRI 001)
#> 6  30  Dark brown             Ghana P.6 (No hits) P.6 (No hits) P.1 (CRI 001)
#> 7  30       Brown Republic of Ghana P.1 (CRI 001) P.1 (CRI 001) P.1 (CRI 001)

There are variations of links() like links_wf_probabilistic() and links_af_probabilistic() for specific use cases such as probabilistic record linkage.

episodes()

Key features;

dfr_2 <- data.frame(date = as.Date("2020-01-01") + c(1:5, 10:15, 20:25))
dfr_2$id.1 <- episodes(
  date = dfr_2$date, case_length = 2,
  episodes_max = 1)
dfr_2$pref <- c(rep(2, 8), 1, rep(2, 8))
dfr_2$id.2 <- episodes(
  date = dfr_2$date, case_length = number_line(-2, 2),
  episodes_max = 1, 
  custom_sort = dfr_2$pref)
dfr_2$id.3 <- episodes(
  date = dfr_2$date, case_length = number_line(-2, 2), 
  episode_type = "rolling", recurrence_length = 1,
  episodes_max = 1, rolls_max = 1)
dfr_2$period <- number_line(dfr_2$date, dfr_2$date + 5)
dfr_2$id.4 <- episodes(
  date = dfr_2$period, case_length = index_window(dfr_2$period),
  episodes_max = 1)
dfr_2
#>          date                              id.1 pref
#> 1  2020-01-02 E.01 2020-01-02 -> 2020-01-04 (C)    2
#> 2  2020-01-03 E.01 2020-01-02 -> 2020-01-04 (D)    2
#> 3  2020-01-04 E.01 2020-01-02 -> 2020-01-04 (D)    2
#> 4  2020-01-05 E.04 2020-01-05 == 2020-01-05 (S)    2
#> 5  2020-01-06 E.05 2020-01-06 == 2020-01-06 (S)    2
#> 6  2020-01-11 E.06 2020-01-11 == 2020-01-11 (S)    2
#> 7  2020-01-12 E.07 2020-01-12 == 2020-01-12 (S)    2
#> 8  2020-01-13 E.08 2020-01-13 == 2020-01-13 (S)    2
#> 9  2020-01-14 E.09 2020-01-14 == 2020-01-14 (S)    1
#> 10 2020-01-15 E.10 2020-01-15 == 2020-01-15 (S)    2
#> 11 2020-01-16 E.11 2020-01-16 == 2020-01-16 (S)    2
#> 12 2020-01-21 E.12 2020-01-21 == 2020-01-21 (S)    2
#> 13 2020-01-22 E.13 2020-01-22 == 2020-01-22 (S)    2
#> 14 2020-01-23 E.14 2020-01-23 == 2020-01-23 (S)    2
#> 15 2020-01-24 E.15 2020-01-24 == 2020-01-24 (S)    2
#> 16 2020-01-25 E.16 2020-01-25 == 2020-01-25 (S)    2
#> 17 2020-01-26 E.17 2020-01-26 == 2020-01-26 (S)    2
#>                                 id.2                              id.3
#> 1  E.01 2020-01-02 == 2020-01-02 (S) E.01 2020-01-02 -> 2020-01-05 (C)
#> 2  E.02 2020-01-03 == 2020-01-03 (S) E.01 2020-01-02 -> 2020-01-05 (D)
#> 3  E.03 2020-01-04 == 2020-01-04 (S) E.01 2020-01-02 -> 2020-01-05 (D)
#> 4  E.04 2020-01-05 == 2020-01-05 (S) E.01 2020-01-02 -> 2020-01-05 (R)
#> 5  E.05 2020-01-06 == 2020-01-06 (S) E.05 2020-01-06 == 2020-01-06 (S)
#> 6  E.06 2020-01-11 == 2020-01-11 (S) E.06 2020-01-11 == 2020-01-11 (S)
#> 7  E.09 2020-01-12 -> 2020-01-16 (D) E.07 2020-01-12 == 2020-01-12 (S)
#> 8  E.09 2020-01-12 -> 2020-01-16 (D) E.08 2020-01-13 == 2020-01-13 (S)
#> 9  E.09 2020-01-12 -> 2020-01-16 (C) E.09 2020-01-14 == 2020-01-14 (S)
#> 10 E.09 2020-01-12 -> 2020-01-16 (D) E.10 2020-01-15 == 2020-01-15 (S)
#> 11 E.09 2020-01-12 -> 2020-01-16 (D) E.11 2020-01-16 == 2020-01-16 (S)
#> 12 E.12 2020-01-21 == 2020-01-21 (S) E.12 2020-01-21 == 2020-01-21 (S)
#> 13 E.13 2020-01-22 == 2020-01-22 (S) E.13 2020-01-22 == 2020-01-22 (S)
#> 14 E.14 2020-01-23 == 2020-01-23 (S) E.14 2020-01-23 == 2020-01-23 (S)
#> 15 E.15 2020-01-24 == 2020-01-24 (S) E.15 2020-01-24 == 2020-01-24 (S)
#> 16 E.16 2020-01-25 == 2020-01-25 (S) E.16 2020-01-25 == 2020-01-25 (S)
#> 17 E.17 2020-01-26 == 2020-01-26 (S) E.17 2020-01-26 == 2020-01-26 (S)
#>                      period                              id.4
#> 1  2020-01-02 -> 2020-01-07 E.01 2020-01-02 -> 2020-01-11 (C)
#> 2  2020-01-03 -> 2020-01-08 E.01 2020-01-02 -> 2020-01-11 (D)
#> 3  2020-01-04 -> 2020-01-09 E.01 2020-01-02 -> 2020-01-11 (D)
#> 4  2020-01-05 -> 2020-01-10 E.01 2020-01-02 -> 2020-01-11 (D)
#> 5  2020-01-06 -> 2020-01-11 E.01 2020-01-02 -> 2020-01-11 (D)
#> 6  2020-01-11 -> 2020-01-16 E.06 2020-01-11 -> 2020-01-16 (S)
#> 7  2020-01-12 -> 2020-01-17 E.07 2020-01-12 -> 2020-01-17 (S)
#> 8  2020-01-13 -> 2020-01-18 E.08 2020-01-13 -> 2020-01-18 (S)
#> 9  2020-01-14 -> 2020-01-19 E.09 2020-01-14 -> 2020-01-19 (S)
#> 10 2020-01-15 -> 2020-01-20 E.10 2020-01-15 -> 2020-01-20 (S)
#> 11 2020-01-16 -> 2020-01-21 E.11 2020-01-16 -> 2020-01-21 (S)
#> 12 2020-01-21 -> 2020-01-26 E.12 2020-01-21 -> 2020-01-26 (S)
#> 13 2020-01-22 -> 2020-01-27 E.13 2020-01-22 -> 2020-01-27 (S)
#> 14 2020-01-23 -> 2020-01-28 E.14 2020-01-23 -> 2020-01-28 (S)
#> 15 2020-01-24 -> 2020-01-29 E.15 2020-01-24 -> 2020-01-29 (S)
#> 16 2020-01-25 -> 2020-01-30 E.16 2020-01-25 -> 2020-01-30 (S)
#> 17 2020-01-26 -> 2020-01-31 E.17 2020-01-26 -> 2020-01-31 (S)

There are variations of episodes() like episodes_wf_splits() for specific use cases such as more efficient handling of duplicate records.

partitions()

Key features;

dfr_3 <- dfr_2["date"]
dfr_3$id.1 <- partitions(
  date = dfr_3$date, 
  window = number_line(as.Date(c("2020-01-10", "2020-01-17")), 
                       as.Date(c("2020-01-12", "2020-01-24")))
  )
dfr_3$id.2 <- partitions(date = dfr_3$date, by = 3, separate = TRUE) 
dfr_3$id.3 <- partitions(date = dfr_3$date, length.out = 3, separate = TRUE)
dfr_3
#>          date      id.1      id.2      id.3
#> 1  2020-01-02 PN.01 (I) PN.18 (I) PN.18 (I)
#> 2  2020-01-03 PN.02 (I) PN.18 (D) PN.18 (D)
#> 3  2020-01-04 PN.03 (I) PN.18 (D) PN.18 (D)
#> 4  2020-01-05 PN.04 (I) PN.19 (I) PN.18 (D)
#> 5  2020-01-06 PN.05 (I) PN.19 (D) PN.18 (D)
#> 6  2020-01-11 PN.06 (I) PN.21 (I) PN.18 (D)
#> 7  2020-01-12 PN.07 (I) PN.21 (D) PN.18 (D)
#> 8  2020-01-13 PN.08 (I) PN.21 (D) PN.18 (D)
#> 9  2020-01-14 PN.09 (I) PN.22 (I) PN.19 (I)
#> 10 2020-01-15 PN.10 (I) PN.22 (D) PN.19 (D)
#> 11 2020-01-16 PN.11 (I) PN.22 (D) PN.19 (D)
#> 12 2020-01-21 PN.12 (I) PN.24 (I) PN.19 (D)
#> 13 2020-01-22 PN.13 (I) PN.24 (D) PN.19 (D)
#> 14 2020-01-23 PN.14 (I) PN.25 (I) PN.19 (D)
#> 15 2020-01-24 PN.15 (I) PN.25 (D) PN.19 (D)
#> 16 2020-01-25 PN.16 (I) PN.25 (D) PN.19 (D)
#> 17 2020-01-26 PN.17 (I) PN.25 (D) PN.19 (D)

Find out more!

Bugs and issues

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.