plotCorrelations {miceRanger}

plotCorrelations

Description

Plot the correlation of imputed values between every combination of datasets for each variable.

Usage

plotCorrelations(
  miceObj,
  vars = names(miceObj$callParams$vars),
  factCorrMetric = "CramerV",
  numbCorrMetric = "pearson",
  ...
)

Arguments

miceObj

an object of class miceDefs, created by the miceRanger function.

vars

the variables you want to plot. Default is to plot all variables. Can be a vector of variable names, or one of 'allNumeric' or 'allCategorical'

factCorrMetric

The correlation metric for categorical variables. Can be one of:

• "CramerV" Cramer's V correlation metric.

• "Chisq" Chi Square test statistic.

• "TschuprowT" Tschuprow's T correlation metric.

• "Phi" (Binary Variables Only) Phi coefficient.

• "YuleY" (Binary Variables Only) Yule's Y, also known as coefficient of colligation

• "YuleQ" (Binary Variables Only) Yule's Q, related to Yule's Y by Q=2Y/(1+Y^2)

numbCorrMetric

The correlation metric for numeric variables. Can be one of:

• "pearson" Pearson's Correlation Coefficient

• "spearman" Spearman's Rank Correlation Coefficient

• "kendall" Kendall's Rank Correlation Coefficient

• "Rsquared" R-squared

...

Other arguments to pass to ggarrange()

Value

an object of class ggarrange.

Examples

data("sampleMiceDefs")
plotCorrelations(sampleMiceDefs)