explore_bivariate: Exploring biviate regression results of a dataframe

In rgardiner90/researchr: Automating Basic Analyses for Social Science Researchers

Description

This function returns either a graph or table of bivariate regression results for a dataset. The results are helpful when trying to first gain an understanding of relationships between a large number of variables.

Usage

explore_bivariate(data, dependent, independent, control = FALSE,
  p_value = 0.05, type = "graph", model_type = "ols")

Arguments

data	A matrix, data frame, or tibble.
dependent	A string character of the dependent variable
independent	A string vector of the different independent variables to test
control	A string character of one control variable that can be used
p_value	The significance threshold for a table output (defaults to 0.05). Graph is fixed at 95 percent confidence intervals
type	Specifies the type of output request. either 'graph' or 'table'
model_type	Specificies whether you have an OLS or logit model

Examples

explore_bivariate(data = mtcars, dependent = "mpg", independent = c("cyl", "disp", "hp", "drat"), control = "gear", p_value = 0.05, type = "table")
explore_bivariate(mtcars, names(mtcars)[1], names(mtcars)[-1])

rgardiner90/researchr documentation built on Nov. 5, 2019, 3:07 a.m.