Skip to contents

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

Source: R/Analyze_NormalApprox.R
Analyze_NormalApprox.Rd

[Stable]

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

More information can be found in The Normal Approximation Method of the KRI Method vignette.

Usage

Analyze_NormalApprox(dfTransformed, strType = "binary")

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"). For this function, dfTransformed should typically be created using Transform_Rate().

strType

character Statistical outcome type. Valid values:

  • "binary" (default)

  • "rate"

Value

data.frame with one row per site with columns: GroupID, Numerator, Denominator, Metric, OverallMetric, Factor, and Score.

Statistical Methods

This function applies funnel plots using asymptotic limits based on the normal approximation of a binomial distribution for the binary outcome, or normal approximation of a Poisson distribution for the rate outcome with volume (the sample sizes or total exposure of the sites) to assess data quality and safety.

Examples

# Binary
dfTransformed <- Transform_Rate(analyticsInput)

dfAnalyzed <- Analyze_NormalApprox(dfTransformed, strType = "binary")
#> `OverallMetric`, `Factor`, and `Score` columns created from normal
#> approximation.

# Rate
dfAnalyzed <- Analyze_NormalApprox(dfTransformed, strType = "rate")
#> `OverallMetric`, `Factor`, and `Score` columns created from normal
#> approximation.