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Flag

Source: R/Flag.R
Flag.Rd

[Stable]

Add columns flagging sites that represent possible statistical outliers when the Identity statistical method is used.

Usage

Flag(
  dfAnalyzed,
  strColumn = "Score",
  vThreshold = c(-3, -2, 2, 3),
  vFlag = c(-2, -1, 0, 1, 2),
  vFlagOrder = c(2, -2, 1, -1, 0)
)

Arguments

dfAnalyzed

data.frame where flags should be added.

strColumn

character Name of the column to use for thresholding. Default: "Score"

vThreshold

numeric Vector of numeric values representing threshold values. Default is c(-3,-2,2,3) which is typical for z-scores.

vFlag

numeric Vector of flag values. There must be one more item in Flag than thresholds - that is length(vThreshold)+1 == length(vFlagValues). Default is c(-2,-1,0,1,2), which is typical for z-scores.

vFlagOrder

numeric Vector of ordered flag values. Output data.frame will be sorted based on flag column using the order provided. NULL (or values that don't match vFlag) will leave the data unsorted. Must have identical values to vFlag. Default is c(2,-2,1,-1,0) which puts largest z-score outliers first in the data set.

Value

data.frame dfAnalyzed is returned with an additional Flag column.

Details

This function provides a generalized framework for flagging sites as part of the GSM data model (see vignette("DataModel")).

Data Specification

Flag is designed to support the input data (dfAnalyzed) from the Analyze_Identity() function. At a minimum, the input data must have a strGroupCol parameter and a numeric strColumn parameter defined. strColumn will be compared to the specified thresholds in vThreshold to define a new Flag column, which identifies possible statistical outliers. If a user would like to see the directionality of those identified points, they can define the strValueColumn parameter, which will assign a positive or negative indication to already flagged points.

The following columns are considered required:

  • GroupID - Group ID; default is SiteID

  • GroupLevel - Group Type

  • strColumn - A column to use for thresholding

The following column is considered optional:

  • strValueColumn - A column to be used for the sign/directionality of the flagging

Examples


dfTransformed <- Transform_Rate(analyticsInput)
dfAnalyzed <- Analyze_NormalApprox(dfTransformed)
#> `OverallMetric`, `Factor`, and `Score` columns created from normal
#> approximation.
dfFlagged <- Flag(dfAnalyzed)
#> ℹ Sorted dfFlagged using custom Flag order: 2.Sorted dfFlagged using custom Flag order: -2.Sorted dfFlagged using custom Flag order: 1.Sorted dfFlagged using custom Flag order: -1.Sorted dfFlagged using custom Flag order: 0.