Partial Regression Plot

Generate a partial regression plot for a specified independent and dependent variable while adjusting for covariates. In addition to the figure, key parameters such as the correlation method, whether relabeling was used, the covariates, R-squared, p-value, and sample size are returned.

Usage

PlotPartialRegressionScatter(
  data,
  IndepVar,
  DepVar,
  covariates = NULL,
  Relabel = TRUE,
  DataFrame = lifecycle::deprecated(),
  Covariates = lifecycle::deprecated()
)

Arguments

data

The dataset to use.

IndepVar

A string specifying the independent variable.

DepVar

A string specifying the dependent variable.

covariates

A character vector of covariate names for adjustment. Defaults to NULL.

Relabel

Logical indicating whether to use labelled names from the data (using sjlabelled::get_label). Defaults to TRUE.

DataFrame

Deprecated (since 19.15.0). Use data instead.

Covariates

Deprecated (since 19.15.0). Use covariates instead.

Value

A list containing:

plot

A ggplot2 object representing the partial regression plot.

method

The correlation method (as provided).

Relabel

Logical; whether relabeling was applied.

Covariates

The vector of covariates.

r2

The R-squared of the partial regression model.

p_value

The p-value for the independent variable coefficient.

n

The sample size (number of complete cases).

equation

The regression equation string.

Examples

data(SampleData)
data(SampleVariableTypes)

Labelled <- RevalueData(SampleData, SampleVariableTypes)$RevaluedData

result <- PlotPartialRegressionScatter(
  Labelled,
  IndepVar = "age",
  DepVar = "AXL",
  covariates = "Adiponectin"
)

result$plot
#> `geom_smooth()` using formula = 'y ~ x'