Create a Forest Plot from Univariate Regression Tables

This function generates a forest plot from the results of MakeUnivariateRegressionTable().

plotForestFromTable() was renamed to PlotForestFromTable() in SciDataReportR 20.5.0 to match the package's Plot* naming convention. It remains available as a backwards-compatible synonym.

Usage

PlotForestFromTable(UnivariateRegressionTables, pSize = 2, Flip = FALSE)

plotForestFromTable(UnivariateRegressionTables, pSize = 2, Flip = FALSE)

Arguments

UnivariateRegressionTables

Either the full list returned by MakeUnivariateRegressionTable() (its Results dataframe is used directly), or a dataframe with the Results columns. Passing a dataframe lets you filter, reorder, or relabel Results before plotting; required columns are OutcomeLabel, TermLabel, Estimate, ConfLow, ConfHigh, and PValue (Significant and ReferenceValue are recomputed if absent). Lists created by older package versions (without a Results element) are still supported.

pSize

Numeric. Size of the points in the plot. Default is 2.

Flip

Logical. If FALSE, outcomes are facets and predictors/terms are rows. If TRUE, predictors/terms are facets and outcomes are rows.

Value

A ggplot object representing the forest plot.

Examples

# \donttest{
data(SampleData)

# Build univariate regression tables to plot
urt <- MakeUnivariateRegressionTable(
  data = SampleData,
  outcome_vars = "AXL",
  predictor_vars = c("age", "Adiponectin", "Alpha_1_Antitrypsin")
)

PlotForestFromTable(urt)


# Or plot a filtered subset of the results
PlotForestFromTable(subset(urt$Results, Predictor != "age"))

# }