Simple linear regression model

Source: R/cv-model-fit.R

This model uses all predictors to model the outcome with lm function

lm_model(
  predictors,
  outcome,
  SESOI_lower = 0,
  SESOI_upper = 0,
  na.rm = FALSE,
  ...
)

Arguments

predictors

Data frame
outcome

Vector
SESOI_lower

Lower smallest effect size of interest threshold
SESOI_upper

Upper smallest effect size of interest threshold
na.rm

Should NAs be removed? Default is FALSE
...

Extra arguments forwarded to lm function

Value

model object

Examples

lm_model(
  predictors = iris[2:3],
  outcome = iris[[1]]
)
#> 
#> Call:
#> stats::lm(formula = .outcome ~ . - 1, data = data)
#> 
#> Coefficients:
#>  Sepal.Width  Petal.Length  
#>       1.2029        0.5691  
#>