Collate: 'as.character.formula.R' 'env.R' 'get.vars.R' 'invert.R'
'rhs.vars.R' 'split.terms.R' 'terms.R' 'toggle.sign.R' 'zzz.R'

person("Caffrey", "Lee", , "cl3802@columbia.edu", c("ctb")),
person("Zichen", "Huang", , "zh2380@columbia.edu", c("ctb")),
person("Anderson", "Nelson", , "an2908@columbia.edu", c("ctb","cre"))
Description: Create a dynamic formula with multiple features. It not only diminishes the time required for modeling and implementing, but also enriches the quality of the result. Many statistical models and analyses in 'R' are implemented through formula objects. The 'formulaic' package creates a unified approach for programmatically and dynamically generating formula objects in 'R'. Users may specify the inputs and outcomes of a model directly, search for variables to include based upon naming patterns, and identify variables to exclude. A wide range of quality checks are implemented to identify issues such as misspecified variables, duplication, a lack of contrast in the inputs, and a large number of levels in categorical data. These issues are documented and reported in a manner that provides greater accountability and useful information to guide an investigators choices in selecting features.

Title: Dynamic Generation and Quality Checks of Formula Objects
Description: Many statistical models and analyses in R are implemented through formula objects. The formulaic package creates a unified approach for programmatically and dynamically generating formula objects. Users may specify the outcome and inputs of a model directly, search for variables to include based upon naming patterns, incorporate interactions, and identify variables to exclude. A wide range of quality checks are implemented to identify issues such as misspecified variables, duplication, a lack of contrast in the inputs, and a large number of levels in categorical data.  Variables that do not meet these quality checks can be automatically excluded from the model.  These issues are documented and reported in a manner that provides greater accountability and useful information to guide an investigation of the data.