Calculate Change

Calculate the change of user-specified metrics from the previous snapshot date. The primary use case of this function is to check for changes in the metrics when determining if continued flags should be actioned.

Usage

CalculateChange(
  dfResults,
  dfResultsLongitudinal = NULL,
  strIDColumns = c("StudyID", "GroupLevel", "GroupID", "MetricID"),
  strSnapshotDateColumn = "SnapshotDate",
  dPrevSnapshotDate = NULL,
  strMetricColumns = c("Numerator", "Denominator", "Metric", "Score", "Flag")
)

Arguments

dfResults

data.frame A stacked summary of analysis pipeline output. Created by passing a list of results returned by gsm.core::Summarize() to BindResults(). Expected columns: GroupID, GroupLevel, Numerator, Denominator, Metric, Score, Flag, MetricID, StudyID, SnapshotDate.

dfResultsLongitudinal

data.frame A stacked summary of analysis pipeline output from the previous snapshot. Created by passing a list of results returned by gsm.core::Summarize() to BindResults(). Expected columns: GroupID, GroupLevel, Numerator, Denominator, Metric, Score, Flag, MetricID, StudyID, SnapshotDate.

strIDColumns

character A vector of column names with which to group results. Default:

• StudyID

• GroupLevel

• GroupID

• MetricID

strSnapshotDateColumn

character The name of the column containing the snapshot date. Default: SnapshotDate.

dPrevSnapshotDate

Date The date of the previous snapshot to be compared. Optional. Default = NULL.

strMetricColumns

character A vector of numeric column names with which calculate change from previous snapshot. Default:

• Numerator

• Denominator

• Metric

• Score

• Flag

Value

data.frame A transposed table of results with a column for each attribute, its value, and the change from the previous snapshot.

Examples

dfResults <- gsm.core::reportingResults |> dplyr::filter(SnapshotDate == "2025-04-01")
dfResultsLongitudinal <- gsm.core::reportingResults |> dplyr::filter(SnapshotDate != "2025-04-01")
dfChChChChanges <- CalculateChange(
  dfResults = dfResults,
  dfResultsLongitudinal = dfResultsLongitudinal
)