Plot Significant Correlations

Generate scatterplots for significant correlations based on a previously generated correlation heatmap.

Usage

plotSigCorrelations(
  data,
  CorrelationHeatmapObject,
  PVar = "P",
  Pthresh = 0.05,
  DataFrame = lifecycle::deprecated()
)

Arguments

data

The dataset used to generate the scatterplots.

CorrelationHeatmapObject

The output of the PlotCorrelationsHeatmap function.

PVar

The name of the column used to filter for significance (default is "P").

Pthresh

The significance threshold (default is 0.05).

DataFrame

Deprecated (since 19.15.0). Use data instead.

Value

A list of scatterplot objects for significant correlations.

Examples

# \donttest{
# Build a correlation heatmap, then plot the significant pairs. Keep the
# predictor and outcome sets disjoint so no variable is correlated with
# itself.
ch <- PlotCorrelationsHeatmap(
  mtcars,
  predictor_vars = c("wt", "hp", "disp"),
  outcome_vars = c("mpg", "qsec")
)

plots <- plotSigCorrelations(mtcars, ch)

# Display the first significant-correlation scatterplot
plots[[1]]

# }