standardized_regression {kim}

Standardized Regression

Description

This function standardizes all variables for a regression analysis (i.e., dependent variable and all independent variables) and then conducts a regression with the standardized variables.

Usage

standardized_regression(
  data = NULL,
  formula = NULL,
  reverse_code_vars = NULL,
  sigfigs = NULL,
  round_digits_after_decimal = NULL,
  round_p = 3,
  pretty_round_p_value = TRUE,
  return_table_upper_half = FALSE,
  round_r_squared = 3,
  round_f_stat = 2,
  prettify_reg_table_col_names = TRUE
)

Arguments

data

a data object (a data frame or a data.table)

formula

a formula object for the regression equation

reverse_code_vars

names of binary variables to reverse code

sigfigs

number of significant digits to round to

round_digits_after_decimal

round to nth digit after decimal (alternative to sigfigs)

round_p

number of decimal places to which to round p-values (default = 3)

pretty_round_p_value

logical. Should the p-values be rounded in a pretty format (i.e., lower threshold: "<.001"). By default, pretty_round_p_value = TRUE.

return_table_upper_half

logical. Should only the upper part of the table be returned? By default, return_table_upper_half = FALSE.

round_r_squared

number of digits after the decimal both r-squared and adjusted r-squared values should be rounded to (default 3)

round_f_stat

number of digits after the decimal the f statistic of the regression model should be rounded to (default 2)

prettify_reg_table_col_names

logical. Should the column names of the regression table be made pretty (e.g., change "std_beta" to "Std. Beta")? (Default = TRUE)

Value

the output will be a data.table showing multiple regression results.

Examples

standardized_regression(data = mtcars, formula = mpg ~ gear * cyl)
standardized_regression(
data = mtcars, formula = mpg ~ gear + gear:am + disp * cyl,
round_digits_after_decimal = 3)