Six Sigma Metrics for Laboratory Performance

Six Sigma methodology for laboratory performance evaluation and quality assessment. Calculates sigma metrics, process capability indices, and quality goal index (QGI) for analytical methods. Supports ISO 15189 compliance and quality improvement initiatives. Essential for laboratory method validation and performance monitoring.

Usage

sigmametrics(
  data,
  bias,
  cv,
  tea,
  analyte,
  laboratory,
  method,
  sigma_calculation = "standard",
  quality_goals = "clia",
  custom_tea = 10,
  confidence_level = 0.95,
  benchmark_comparison = TRUE,
  process_capability = TRUE,
  quality_goal_index = TRUE,
  method_validation = TRUE,
  improvement_recommendations = TRUE,
  regulatory_compliance = TRUE,
  cost_of_quality = FALSE,
  defect_rates = TRUE,
  control_planning = FALSE,
  sigma_plots = TRUE,
  normalized_plots = TRUE,
  quality_scorecard = TRUE
)

Arguments

data: the data as a data frame
bias: Method bias as percentage from target value
cv: Coefficient of variation (precision) as percentage
tea: Total allowable error specification as percentage
analyte: Analyte or test name for identification
laboratory: Laboratory or site identifier for comparative analysis
method: Analytical method identifier
sigma_calculation: Method for calculating sigma metrics
quality_goals: Source for quality goal specifications
custom_tea: Custom total allowable error specification
confidence_level: Confidence level for uncertainty calculations
benchmark_comparison: Compare against benchmark sigma levels
process_capability: Calculate Cp, Cpk, and other capability indices
quality_goal_index: Calculate quality goal index metrics
method_validation: Evaluate method performance for validation
improvement_recommendations: Provide specific improvement recommendations
regulatory_compliance: Assess compliance with regulatory standards
cost_of_quality: Estimate cost implications of quality levels
defect_rates: Calculate expected defect rates per million
control_planning: Generate QC planning recommendations
sigma_plots: Create sigma metric and capability plots
normalized_plots: Generate normalized operating specifications chart
quality_scorecard: Create comprehensive quality scorecard visualization

Value

A results object containing:

`results$instructions`					a html
`results$dataInfo`					a table
`results$sigmaResults`					a table
`results$processCapability`					a table
`results$qualityGoalIndex`					a table
`results$benchmarkComparison`					a table
`results$methodValidation`					a table
`results$regulatoryCompliance`					a table
`results$improvementRecommendations`					a table
`results$defectRateAnalysis`					a table
`results$costOfQuality`					a table
`results$controlPlanning`					a table
`results$sigmaPlot`					an image
`results$normalizedChart`					an image
`results$qualityScorecard`					an image
`results$methodExplanation`					a html

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

results$dataInfo$asDF

as.data.frame(results$dataInfo)

Usage

Arguments

Value

Examples