Validate Power Analysis Results — check_power

Validates that power analysis results would have sufficient data after applying cost and power filters. Returns the original unfiltered data if validation passes.

Usage

check_power_results(
  power_df,
  cost_constraint,
  cost_precision,
  power_target,
  power_precision
)

Arguments

power_df: Data frame. Power analysis results with columns including overall_power, total_cost.
cost_constraint: Numeric. Maximum budget constraint in dollars. Set to NULL to disable cost filtering.
cost_precision: Numeric. Cost utilization factor. Filters designs with total cost \le cost_precision × cost_constraint.
power_target: Numeric. Target statistical power.
power_precision: Numeric. Acceptable precision around power target. Filters designs with power \ge power_target - power_precision.

Value

Data frame. The original unfiltered power analysis results (if validation passes).

Details

This function validates filtering viability without actually filtering:

Cost check: Verifies that total_cost \le cost_precision × cost_constraint would leave at least one row (only when cost_constraint is not NULL)
Power check: Verifies that overall_power \ge power_target - power_precision would leave at least one row

Throws informative errors when validation checks fail, otherwise returns the original data.