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Create date variable for MockData

Source: R/create_date_var.R
create_date_var.Rd

Creates a mock date variable based on specifications from variable_details.

Usage

create_date_var(
  var_row = NULL,
  details_subset = NULL,
  n = NULL,
  seed = NULL,
  source_format = "analysis",
  df_mock = NULL,
  var_raw = NULL,
  cycle = NULL,
  variable_details = NULL,
  variables = NULL,
  length = NULL,
  prop_NA = NULL,
  prop_invalid = NULL,
  distribution = "uniform"
)

Arguments

var_row

data.frame. Single row from mock_data_config (contains variable metadata)

details_subset

data.frame. Rows from mock_data_config_details for this variable

n

integer. Number of observations to generate

seed

integer. Random seed for reproducibility. If NULL, uses global seed.

source_format

character. Format to simulate post-import data: "analysis" (R Date objects), "csv" (character ISO strings), "sas" (numeric days since 1960-01-01). Default: "analysis".

df_mock

data.frame. The current mock data (to check if variable already exists)

Configuration v0.1 format (LEGACY):

var_raw

character. The RAW variable name (as it appears in source data)

cycle

character. The database or cycle identifier (e.g., "cycle1", "HC1")

variable_details

data.frame. Variable details metadata

variables

data.frame. Variables metadata (optional, for validation)

length

integer. The desired length of the mock data vector

prop_NA

numeric. Optional. Proportion of NA values (0 to 1). If NULL, no NAs introduced.

prop_invalid

numeric. Optional. Proportion of invalid out-of-period dates (0 to 1). If NULL, no invalid dates generated.

distribution

character. Distribution type: "uniform" (default), "gompertz", or "exponential"

Value

data.frame with one column (the new date variable), or NULL if:

  • Variable details not found (v0.1 only)

  • Variable already exists in df_mock

  • No valid date range found

Details

Configuration v0.2 format (NEW):

v0.2 format (NEW):

  • Extracts date_start and date_end from details_subset

  • Generates dates uniformly distributed between start and end

  • Applies missing codes with apply_missing_codes()

  • Adds garbage using make_garbage() if garbage rows present

  • Supports fallback mode: uniform distribution [2000-01-01, 2025-12-31] when details_subset is NULL

v0.1 format (LEGACY):

  • Uses get_variable_details_for_raw() to find variable specifications

  • Parses SAS date format from recStart: "[01JAN2001, 31MAR2017]"

  • Supports "uniform", "gompertz", or "exponential" distribution

  • Handles prop_NA and prop_invalid parameters

The function auto-detects which format based on parameter names.

See also

Other generators: create_cat_var(), create_con_var(), create_survival_dates()

Examples

if (FALSE) { # \dontrun{
# v0.2 format - called by create_mock_data()
config <- read_mock_data_config("mock_data_config.csv")
details <- read_mock_data_config_details("mock_data_config_details.csv")
var_row <- config[config$variable == "index_date", ]
details_subset <- get_variable_details(details, variable_name = "index_date")
mock_var <- create_date_var(var_row, details_subset, n = 1000, seed = 123)

# v0.1 format (legacy)
mock_death_date <- create_date_var(
  var_raw = "death_date",
  cycle = "ices",
  variable_details = variable_details,
  length = 1000,
  df_mock = existing_data,
  prop_NA = 0.02,
  distribution = "gompertz"
)
} # }