Intermediate Precision (Between-Run Precision)

Calculates intermediate precision statistics for measurements performed under varying conditions (different days, analysts, or instruments).

Usage

measure_intermediate_precision(
  data,
  response_col,
  factors,
  group_col = NULL,
  conf_level = 0.95
)

Arguments

data

A data frame containing measurements with factor columns.

response_col

Name of the column containing the response values.

factors

Character vector of factor column names (e.g., c("day", "analyst")).

group_col

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

conf_level

Confidence level for intervals. Default is 0.95.

Value

A measure_precision object containing variance components and precision estimates:

• component: Name of the variance component

• variance: Estimated variance

• percent_variance: Percentage of total variance

• sd: Standard deviation (square root of variance)

• cv: Coefficient of variation (%) for that component

Details

Intermediate precision quantifies the variability due to different conditions within the same laboratory. This typically includes:

• Different days

• Different analysts

• Different equipment (of the same type)

The function uses a one-way or nested ANOVA approach to estimate variance components. For more complex designs, consider using mixed effects models with the lme4 package.

See also

measure_repeatability(), measure_reproducibility()

Other precision: measure_gage_rr(), measure_repeatability(), measure_reproducibility()

Examples

# Intermediate precision across days
set.seed(123)
data <- data.frame(
  day = rep(1:5, each = 6),
  concentration = rnorm(30, mean = 100, sd = 3) +
    rep(rnorm(5, 0, 2), each = 6)  # Day effect
)
measure_intermediate_precision(data, "concentration", factors = "day")
#> measure_precision: intermediate 
#> ──────────────────────────────────────────────────────────────────────────────── 
#> 
#> Variance Components:
#>   day: 0 (0%)
#>   Residual: 9.311 (100%)
#> 
#> CV by component:
#>   day: 0%
#>   Residual: 3%