Generates a mock person table and integrates it into an existing CDM object.

This function creates a mock person table with specified characteristics for each individual, including a randomly assigned date of birth within a given range and gender based on specified proportions. It populates the CDM object's person table with these entries, ensuring each record is uniquely identified.

Usage

mockPerson(
  cdm = mockCdmReference(),
  nPerson = 10,
  birthRange = as.Date(c("1950-01-01", "2000-12-31")),
  proportionFemale = 0.5,
  seed = NULL
)

Arguments

cdm: A local cdm_reference object used as the base structure to update.
nPerson: An integer specifying the number of mock persons to create in the person table. This defines the scale of the simulation and allows for the creation of datasets with varying sizes.
birthRange: A date range within which the birthdays of the mock persons will be randomly generated. This should be provided as a vector of two dates (as.Date format), specifying the start and end of the range.
proportionFemale: A numeric value between 0 and 1 indicating the proportion of the persons who are female. For example, a value of 0.5 means approximately 50% of the generated persons will be female. This helps simulate realistic demographic distributions.
seed: An optional integer used to set the random seed for reproducibility. If NULL, the seed is not set.

Value

A modified cdm_reference object.

Examples

# \donttest{
library(omock)
library(dplyr)
cdm <- mockPerson(cdm = mockCdmReference(), nPerson = 10)

# View the generated person data
cdm$person |>
glimpse()
#> Rows: 10
#> Columns: 18
#> $ person_id                   <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
#> $ gender_concept_id           <int> 8532, 8532, 8507, 8532, 8532, 8532, 8532, …
#> $ year_of_birth               <int> 1966, 1972, 1964, 1997, 1985, 1979, 1992, …
#> $ month_of_birth              <int> 4, 6, 3, 8, 11, 8, 11, 4, 8, 4
#> $ day_of_birth                <int> 14, 27, 19, 30, 2, 17, 6, 18, 17, 27
#> $ race_concept_id             <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ ethnicity_concept_id        <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ birth_datetime              <dttm> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ location_id                 <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ provider_id                 <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ care_site_id                <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ person_source_value         <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ gender_source_value         <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ gender_source_concept_id    <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ race_source_value           <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ race_source_concept_id      <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ ethnicity_source_value      <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
#> $ ethnicity_source_concept_id <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
# }