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

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

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 |

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.

#> # A tibble: 1 × 3 #> `(Intercept)` wt qsec #> <dbl> <dbl> <dbl> #> 1 19.7 -5.05 0.929