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Accuracy Assessment

Source: R/accuracy.R
measure_accuracy.Rd

Calculates accuracy metrics including bias, recovery, and confidence intervals for method validation.

Usage

measure_accuracy(
  data,
  measured_col,
  reference_col,
  group_col = NULL,
  conf_level = 0.95
)

Arguments

data

A data frame containing measured and reference values.

measured_col

Name of the column containing measured values.

reference_col

Name of the column containing reference/nominal values.

group_col

Optional grouping column (e.g., concentration level).

conf_level

Confidence level for intervals. Default is 0.95.

Value

A measure_accuracy object containing:

  • n: Number of observations

  • mean_measured: Mean of measured values

  • mean_reference: Mean of reference values

  • bias: Absolute bias (measured - reference)

  • bias_pct: Relative bias as percentage

  • recovery: Recovery percentage (measured/reference * 100)

  • recovery_ci_lower, recovery_ci_upper: Confidence interval for recovery

Details

Accuracy expresses the closeness of agreement between a measured value and a reference value. It is typically assessed using:

  • Bias: Systematic difference from the reference value

  • Recovery: Percentage of the reference value that is measured

ICH Q2 Requirements

Accuracy should be assessed at a minimum of 3 concentration levels covering the specified range (typically 80-120% of the target).

See also

measure_linearity(), measure_carryover()

Other accuracy: measure_carryover(), measure_linearity()

Examples

# Accuracy at multiple levels
set.seed(123)
data <- data.frame(
  level = rep(c("low", "mid", "high"), each = 5),
  nominal = rep(c(10, 50, 100), each = 5),
  measured = c(
    rnorm(5, 10.2, 0.3),
    rnorm(5, 49.5, 1.5),
    rnorm(5, 101, 3)
  )
)

result <- measure_accuracy(data, "measured", "nominal", group_col = "level")
print(result)
#> measure_accuracy
#> ──────────────────────────────────────────────────────────────────────────────── 
#> 
#> Group: low 
#>   n = 5 
#>   Mean measured = 10.26 
#>   Mean reference = 10 
#>   Bias = 0.2581 ( 2.6 %)
#>   Recovery = 103 %
#>   Recovery 95% CI: [100%, 106%]
#> 
#> Group: mid 
#>   n = 5 
#>   Mean measured = 49.43 
#>   Mean reference = 50 
#>   Bias = -0.5665 ( -1.1 %)
#>   Recovery = 99 %
#>   Recovery 95% CI: [95%, 103%]
#> 
#> Group: high 
#>   n = 5 
#>   Mean measured = 101.9 
#>   Mean reference = 100 
#>   Bias = 1.924 ( 1.9 %)
#>   Recovery = 102 %
#>   Recovery 95% CI: [100%, 104%]
#>