# Install the latest CRAN release
install.packages("diyar")
# Or, install the development version from GitHub
install.packages("devtools")
devtools::install_github("OlisaNsonwu/diyar")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:
links() - link records with no relevance to an index
record. For example, deterministic record linkageepisodes() - link records in relation to an index
record. For example, contact and network analysis.partitions() - link records in relation to a fixed
interval.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_criteria().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 ...) OR not.equal(30,30 ...)
#> }
sub.cri.3
#> {
#> {
#> exact(hair.color) OR age.range(age)
#> } AND
#> {
#> last.word(Republic of Ghana,France ...) OR not.equal(30,30 ...)
#> }
#> }
dfr_stages$id.3 <- links(
criteria = "place_holder",
sub_criteria = list("cr1" = sub.cri.3)
)
dfr_stages
#> age hair_colour branch_office id.1 id.2 id.3
#> 1 30 Brown Republic of Ghana P.1 (CRI 001) P.1 (CRI 001) P.1 (CRI 001)
#> 2 30 Teal France P.4 (CRI 002) P.2 (CRI 001) P.2 (CRI 001)
#> 3 30 <NA> <NA> P.3 (No hits) P.3 (No hits) P.3 (No hits)
#> 4 30 Green <NA> P.4 (CRI 001) P.2 (CRI 002) P.4 (No hits)
#> 5 30 Green France P.4 (CRI 001) P.2 (CRI 001) P.2 (CRI 001)
#> 6 30 Dark brown Ghana P.6 (No hits) P.6 (No hits) P.1 (CRI 001)
#> 7 30 Brown Republic of Ghana P.1 (CRI 001) P.1 (CRI 001) P.1 (CRI 001)There are variations of links() like
links_wf_probabilistic() and
links_sv_probabilistic() for specific use cases such as
probabilistic record linkage.
Key features;
dfr_2 <- data.frame(date = as.Date("2020-01-01") + c(1:5, 10:15, 20:25))
dfr_2$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$period),
episodes_max = 1)
dfr_2
#> date id.1 pref id.2 id.3 period id.4
#> 1 2020-01-02 E.01 (C) 2 E.01 (S) E.01 (C) 2020-01-02 -> 2020-01-07 E.01 (C)
#> 2 2020-01-03 E.01 (D) 2 E.02 (S) E.01 (D) 2020-01-03 -> 2020-01-08 E.01 (D)
#> 3 2020-01-04 E.01 (D) 2 E.03 (S) E.01 (D) 2020-01-04 -> 2020-01-09 E.01 (D)
#> 4 2020-01-05 E.04 (S) 2 E.04 (S) E.01 (R) 2020-01-05 -> 2020-01-10 E.01 (D)
#> 5 2020-01-06 E.05 (S) 2 E.05 (S) E.05 (S) 2020-01-06 -> 2020-01-11 E.01 (D)
#> 6 2020-01-11 E.06 (S) 2 E.06 (S) E.06 (S) 2020-01-11 -> 2020-01-16 E.06 (S)
#> 7 2020-01-12 E.07 (S) 2 E.09 (D) E.07 (S) 2020-01-12 -> 2020-01-17 E.07 (S)
#> 8 2020-01-13 E.08 (S) 2 E.09 (D) E.08 (S) 2020-01-13 -> 2020-01-18 E.08 (S)
#> 9 2020-01-14 E.09 (S) 1 E.09 (C) E.09 (S) 2020-01-14 -> 2020-01-19 E.09 (S)
#> 10 2020-01-15 E.10 (S) 2 E.09 (D) E.10 (S) 2020-01-15 -> 2020-01-20 E.10 (S)
#> 11 2020-01-16 E.11 (S) 2 E.09 (D) E.11 (S) 2020-01-16 -> 2020-01-21 E.11 (S)
#> 12 2020-01-21 E.12 (S) 2 E.12 (S) E.12 (S) 2020-01-21 -> 2020-01-26 E.12 (S)
#> 13 2020-01-22 E.13 (S) 2 E.13 (S) E.13 (S) 2020-01-22 -> 2020-01-27 E.13 (S)
#> 14 2020-01-23 E.14 (S) 2 E.14 (S) E.14 (S) 2020-01-23 -> 2020-01-28 E.14 (S)
#> 15 2020-01-24 E.15 (S) 2 E.15 (S) E.15 (S) 2020-01-24 -> 2020-01-29 E.15 (S)
#> 16 2020-01-25 E.16 (S) 2 E.16 (S) E.16 (S) 2020-01-25 -> 2020-01-30 E.16 (S)
#> 17 2020-01-26 E.17 (S) 2 E.17 (S) E.17 (S) 2020-01-26 -> 2020-01-31 E.17 (S)There are variations of episodes() like
episodes_wf_splits() for specific use cases such as more
efficient handling of duplicate records.
Key features;
dfr_3 <- dfr_2["date"]
dfr_3$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 (S) PN.01 (I) PN.01 (I)
#> 2 2020-01-03 PN.02 (S) PN.01 (D) PN.01 (D)
#> 3 2020-01-04 PN.03 (S) PN.01 (D) PN.01 (D)
#> 4 2020-01-05 PN.04 (S) PN.04 (I) PN.01 (D)
#> 5 2020-01-06 PN.05 (S) PN.04 (D) PN.01 (D)
#> 6 2020-01-11 PN.06 (I) PN.06 (I) PN.06 (I)
#> 7 2020-01-12 PN.06 (D) PN.06 (D) PN.06 (D)
#> 8 2020-01-13 PN.08 (S) PN.06 (D) PN.06 (D)
#> 9 2020-01-14 PN.09 (S) PN.09 (I) PN.06 (D)
#> 10 2020-01-15 PN.10 (S) PN.09 (D) PN.06 (D)
#> 11 2020-01-16 PN.11 (S) PN.09 (D) PN.06 (D)
#> 12 2020-01-21 PN.06 (D) PN.12 (I) PN.12 (I)
#> 13 2020-01-22 PN.06 (D) PN.12 (D) PN.12 (D)
#> 14 2020-01-23 PN.06 (D) PN.14 (I) PN.12 (D)
#> 15 2020-01-24 PN.06 (D) PN.14 (D) PN.12 (D)
#> 16 2020-01-25 PN.16 (S) PN.14 (D) PN.12 (D)
#> 17 2020-01-26 PN.17 (S) PN.14 (D) PN.12 (D)Other useful functions include in the diyar package are
combi() and sets().
Find out more!
vignette("number_line")vignette("episodes")vignette("links")vignette("panes")Please report any bug or issues with using this package here.