Check Cross-Price Data for Unsystematic Responding — check_systematic

Modern interface for screening cross-price data with standardized output vocabulary aligned with check_systematic_demand().

Usage

check_systematic_cp(
  data,
  trend_threshold = 0.025,
  bounce_threshold_down = 0.1,
  bounce_threshold_up = 0.1,
  bounce_threshold_none = 0.1,
  consecutive_zeros = 2,
  consecutive_nonzeros = 2,
  expected_down = FALSE,
  x_var = "x",
  y_var = "y",
  id_var = "id"
)

Arguments

data: Data frame with columns: id (optional), x (price), y (consumption).
trend_threshold: Numeric. Threshold for trend detection. Default 0.025.
bounce_threshold_down: Numeric. Bounce threshold for upward trends. Default 0.1.
bounce_threshold_up: Numeric. Bounce threshold for downward trends. Default 0.1.
bounce_threshold_none: Numeric. Bounce threshold when no trend. Default 0.1.
consecutive_zeros: Integer. Zeros for reversal detection. Default 2.
consecutive_nonzeros: Integer. Non-zeros for return detection. Default 2.
expected_down: Logical. Suppress reversal detection if TRUE. Default FALSE.
x_var: Character. Name of the price column. Default "x".
y_var: Character. Name of the consumption column. Default "y".
id_var: Character. Name of the subject identifier column. Default "id".

Value

An object of class beezdemand_systematicity with the same structure as check_systematic_demand(), with type = "cp".

Details

If the data contains an id column (or column specified by id_var), each unique ID is checked separately. Otherwise, the entire dataset is treated as a single pattern.

For cross-price data, the wrapper preserves the legacy meaning of check_unsystematic_cp():

trend_direction and bounce_direction are taken directly from the legacy function outputs.
trend_pass is set to NA because cross-price systematicity does not use a separate trend “pass/fail” criterion in the same way as purchase-task screening; instead, trend classification determines which bounce rule applies.
bounce_stat is reported as the proportion relevant to the legacy bounce rule for the detected trend_direction (or expected_down case), computed from the legacy bounce counts and the number of price steps.

Examples

data(etm)
check <- check_systematic_cp(etm)