Indicate if a certain record is within the observation period

Usage

addInObservation(
  x,
  indexDate = "cohort_start_date",
  window = c(0, 0),
  completeInterval = FALSE,
  nameStyle = "in_observation",
  name = NULL,
  type = "numeric"
)

Arguments

x: A table containing individuals in a CDM reference.
indexDate: Name of a date column in x, or a single date to use for all rows, used as the reference date.
window: Window or windows of time relative to indexDate to consider.
completeInterval: If TRUE, individuals must be observed for the full requested interval.
nameStyle: Naming pattern for the added column or columns. It should include the required formatting variables. If more than one tableName is provided, it must include {table_name}.
name: Name of the new table. If NULL, a temporary table is returned.
type: Type of the created column(s). Counts, days, age, and observation durations can be "numeric" or "integer". Flag columns can also be "logical". Field columns can use "auto" to preserve the source type, or can be converted to "numeric", "integer", "logical", or "character".

Value

Cohort table with an added column assessing observation. Values are 1/TRUE in observation and 0/FALSE otherwise, according to type.

Examples

# \donttest{
library(PatientProfiles)

cdm <- mockPatientProfiles(source = "duckdb")
#> duckdb keeps downloaded extensions and secrets in a temporary directory:
#> ℹ /tmp/Rtmp1nF3JK/duckdb
#> This is removed when the R session ends.
#> • Extensions are re-downloaded each session.
#> • Secrets are lost.
#> ℹ Run duckdb(shared_home = TRUE) (or create ~/.duckdb) to keep them (suitable for most users).
#> ℹ Run duckdb(shared_home = FALSE) to accept the temporary directory (and silence this message).
#> ℹ See ?duckdb_storage for details and alternatives.

cdm$cohort1 |>
  addInObservation()
#> # A query:  ?? x 5
#> # Database: DuckDB 1.5.5 [unknown@Linux 6.17.0-1020-azure:R 4.6.1/:memory:]
#>    cohort_definition_id subject_id cohort_start_date cohort_end_date
#>                   <int>      <int> <date>            <date>         
#>  1                    1         10 1913-11-03        1914-02-14     
#>  2                    3          7 1960-09-05        1961-11-29     
#>  3                    1          3 1936-06-17        1968-11-04     
#>  4                    3          2 1961-11-05        1968-06-22     
#>  5                    1          8 1931-03-08        1940-07-08     
#>  6                    3          6 1955-09-15        1956-05-02     
#>  7                    3          1 1912-06-23        1915-11-18     
#>  8                    1          5 1980-07-11        1981-10-29     
#>  9                    1          9 1932-10-20        1935-07-22     
#> 10                    2          4 1980-09-14        1997-09-25     
#> # ℹ 1 more variable: in_observation <dbl>

# }