BiVariAn (version 1.0.3)

auto_corr_cont: Generates automatic scatterplot with correlation plot

Description

Automatically generates correlation plots of continuous variables from a database and a reference variable. The names of the variables are set to the names defined in the database. As a result, graphs generated with the default theme "theme_serene" will be obtained. In this function, the user must define each variable label with "label" function from "table1" package

Usage

auto_corr_cont(
  data,
  referencevar = NULL,
  point_args = list(),
  smooth_args = list(),
  theme_func = theme_serene,
  lang_labs = c("EN", "SPA")
)

Value

Returns a list containing barplots as ggplot2 objects. Objects can be accessed via $ operator.

Arguments

data

Dataframe from which variables will be extracted

referencevar

Reference variable. Must be continuous variable as string (quoted)

point_args

List containing extra arguments to be passed to geom_point function. If no specified, only "stat="identity"" will be passed

smooth_args

List containing extra arguments to be passed to geom_smooth function. If no specified, only "method="lm"" will be passed

theme_func

Theme to display plots. Default is "theme_serene"

lang_labs

Language to display title lab. Default is Spanish.

Author

JMCR

Examples

data <- data.frame(group = rep(letters[1:2], 30),
var1 = rnorm(30, mean = 15, sd = 5),
var2 = rnorm(30, mean = 20, sd = 2),
var3 = rnorm(30, mean = 10, sd = 1),
var4 = rnorm(30, mean = 5, sd =2))

cont_corrplot <- auto_corr_cont(data = data, referencevar = "var1", lang_labs = "EN")

# Call to show all storaged plots
cont_corrplot

# Call to show one individual plot
cont_corrplot$var2