Find possible transformation of model variables

This functions checks whether any transformation, such as log- or exp-transforming, was applied to the response variable (dependent variable) in a regression formula. Optionally, all model terms can also be checked for any such transformation. Currently, following patterns are detected: log, log1p, log2, log10, exp, expm1, sqrt, log(y+<number>), log-log, power (e.g. to 2nd power, like I(y^2)), inverse (like 1/y), scale (e.g., y/3), and box-cox (e-g-, (y^lambda - 1) / lambda).

Usage

find_transformation(x, ...)

# Default S3 method
find_transformation(x, include_all = FALSE, ...)

Arguments

x

A regression model or a character string of the formulation of the (response) variable.

...

Currently not used.

include_all

Logical, if TRUE, does not only check the response variable, but all model terms.

Value

A string, with the name of the function of the applied transformation. Returns "identity" for no transformation, and e.g. "log(y+3)" when a specific values was added to the response variables before log-transforming. For unknown transformations, returns NULL.

Examples

# identity, no transformation
model <- lm(Sepal.Length ~ Species, data = iris)
find_transformation(model)
#> [1] "identity"

# log-transformation
model <- lm(log(Sepal.Length) ~ Species, data = iris)
find_transformation(model)
#> [1] "log"

# log+2
model <- lm(log(Sepal.Length + 2) ~ Species, data = iris)
find_transformation(model)
#> [1] "log(x+2)"

# find transformation for all model terms
model <- lm(mpg ~ log(wt) + I(gear^2) + exp(am), data = mtcars)
find_transformation(model, include_all = TRUE)
#> $response
#>        mpg 
#> "identity" 
#> 
#> $conditional
#>      wt    gear      am 
#>   "log" "power"   "exp" 
#> 

# inverse, response provided as character string
find_transformation("1 / y")
#> [1] "inverse"