Funnel Plot Analysis with Normal Approximation for Binary and Rate Outcomes.

Creates analysis results data for percentage/rate data using funnel plot method with normal approximation.

Usage

Analyze_OneSideProp(dfTransformed, nPropRate = 0.1, nNumDeviations = 3)

Arguments

dfTransformed: data.frame Transformed data for analysis. Data should have one record per site with expected columns: GroupID, GroupLevel, Numerator, Denominator, and Metric. For more details see the Data Model vignette: vignette("DataModel", package = "gsm.core"). For this function, dfTransformed should typically be created using gsm.core::Transform_Rate().
nPropRate: a numeric, between 0 and 1, that represents a proportion of comparison, e.g. a historic screen failure rate
nNumDeviations: a numeric, e.g. '3', standard deviations away from the value provided in nPropRate to calculate a threshold to which the Metric should be flagged

Value

data.frame with one row per site with columns: GroupID, GroupLevel, Numerator, Denominator, Metric, upper_funnel and flag

Statistical Methods

This function applies funnel plots using a fixed proportion/rate and number of standard deviations according to the one-sided Z proportion test.

Examples

# Binary
dftransformed <- tibble::tribble(
  ~GroupID, ~GroupLevel, ~Numerator, ~Denominator, ~Metric,
  "ABC", "Study", 25, 100, 0.25
)

dfAnalyzed <- Analyze_OneSideProp(dftransformed, nPropRate = 0.01, nNumDeviations = 3)