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Practical tool for evaluating sampling adequacy and statistical power in clinicopathological research.

Usage

samplingerror(
  data,
  detectionSensitivity = 95,
  biologicalVarianceCV = 15,
  sampleSize = 10,
  eventFrequency = 5,
  referenceVolume = 100,
  sampleVolume = 10,
  calculationMode = "theoretical",
  sampleData = NULL,
  targetError = 10,
  showErrorComponents = TRUE,
  showOptimization = TRUE,
  showVisualization = TRUE,
  showMethodology = TRUE,
  showReferences = FALSE,
  confidenceLevel = 0.95
)

Arguments

data

.

detectionSensitivity

Probability of correctly detecting/identifying an event (e.g., tumor cell). 100 percent means perfect detection, 95 percent means 5 percent false negative rate.

biologicalVarianceCV

Coefficient of variation representing tissue heterogeneity. Low (5-10 percent) = homogeneous tissue, Medium (15-25 percent) = moderate heterogeneity, High (>30 percent) = highly heterogeneous tissue.

sampleSize

Number of samples/sections/areas examined.

eventFrequency

Proportion of sample containing the event of interest (e.g., percent of tissue with tumor, percent positive cells).

referenceVolume

Total reference space being sampled (e.g., organ volume, total tissue area).

sampleVolume

Volume/area of each sample examined (same units as reference volume).

calculationMode

Theoretical: Calculate error from theoretical parameters. Empirical: Estimate error components from actual data.

sampleData

Actual measurements from samples (for empirical calculation).

targetError

Desired maximum total sampling error. Used for sample size recommendations.

showErrorComponents

Display breakdown of the three error components: E(Ne), E(B(n)), E(Ne/sv).

showOptimization

Calculate optimal sample sizes for different target error rates.

showVisualization

.

showMethodology

.

showReferences

.

confidenceLevel

.

Value

A results object containing:

results$errorSummarya table
results$errorComponentsa table
results$optimizationa table
results$plotan image
results$methodologya html
results$referencesa html

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$errorSummary$asDF

as.data.frame(results$errorSummary)

Details

Calculates sampling efficiency and error rates according to Kayser (2009).