Fits a Linear Regression model — linear_regression

It uses 'tidyeval' and 'dplyr' to create a linear regression model.

linear_regression_db(df, y_var = NULL, sample_size = NULL, auto_count = FALSE)

Arguments

df: A Local or remote data frame
y_var: Dependent variable
sample_size: Prevents a table count. It is only used for models with three or more independent variables
auto_count: Serves as a safeguard in case sample_size is not passed inadvertently. Defaults to FALSE. If it is ok for the function to count how many records are in the sample, then set to TRUE. It is only used for models with three or more independent variables

Details

The linear_regression_db() function only calls one of three unexported functions. The function used is determined by the number of independent variables. This is so any model of one or two variables can use a simpler formula, which in turn will have less SQL overhead.

Examples

library(dplyr)

mtcars %>%
  select(mpg, wt, qsec) %>%
  linear_regression_db(mpg)
#> # A tibble: 1 × 3
#>   `(Intercept)`    wt  qsec
#>           <dbl> <dbl> <dbl>
#> 1          19.7 -5.05 0.929