Generate Adjusted and Unadjusted Service Counts by Year

generate_adjustment_values calculates yearly unadjusted and adjusted service counts for each indicator within a cd_data dataset, applying the specified adjustment type. It provides a comparison of raw and adjusted values for analysis purposes.

Usage

generate_adjustment_values(
  .data,
  adjustment = c("default", "custom", "none"),
  k_factors = NULL
)

Arguments

.data

A cd_data dataframe containing service data for adjustments.

adjustment

A character string specifying the adjustment type:

• "default": Applies preset k-factors (e.g., 0.25) for each indicator group.

• "custom": Uses user-specified k_factors values for each indicator group.

• "none": Skips adjustments, returning only the raw data.

k_factors

A named numeric vector of custom k-factor values between 0 and 1 for each indicator group (e.g., c(anc = 0.3, idelv = 0.2, ...)). Required if adjustment = "custom".

Value

A cd_adjustment_values tibble containing:

• Columns for unadjusted values, suffixed with _raw.

• Columns for adjusted values, suffixed with _adj.

• A year column indicating the year of each count.

Details

This function performs the following steps:

1. Data Validation: Ensures .data is of the cd_data class and adjustment is correctly specified.

2. Unadjusted Summation: Calculates the yearly sums of unadjusted service counts.

3. Adjusted Summation: Applies adjust_service_data() to compute adjusted values, then calculates the yearly sums.

4. Combining Results: Merges unadjusted and adjusted yearly counts for comparison.

See also

adjust_service_data() for the detailed adjustment function.

Examples

if (FALSE) { # \dontrun{
# Generate adjustment values with default k-factors
adjustment_values_default <- generate_adjustment_values(data, adjustment = "default")

# Generate adjustment values with custom k-factors
custom_k <- c(anc = 0.3, idelv = 0.2, pnc = 0.35, vacc = 0.4, opd = 0.3, ipd = 0.25)
adjustment_values_custom <-
  generate_adjustment_values(data, adjustment = "custom", k_factors = custom_k)

# Generate unadjusted values only
unadjusted_values <- generate_adjustment_values(data, adjustment = "none")
} # }