combine_predictors function

Generate model formulas by combining predictors

lifecycle::badge("maturing")

Create model formulas with every combination of your fixed effects, along with the dependent variable and random effects. 259,358 formulas have been precomputed with two- and three-way interactions for up to 8 fixed effects, with up to 5 included effects per formula. Uses the + and * operators, so lower order interactions are automatically included.

combine_predictors(
  dependent,
  fixed_effects,
  random_effects = NULL,
  max_fixed_effects = 5,
  max_interaction_size = 3,
  max_effect_frequency = NULL
)

Arguments

• dependent: Name of dependent variable. (Character)

• fixed_effects: list of fixed effects. (Character)

  Max. limit of 8 effects when interactions are included !

  A fixed effect name cannot contain: white spaces, "*" or "+".

  Effects in sublists will be interchanged. This can be useful, when we have multiple versions of a predictor (e.g. x1 and log(x1)) that we do not wish to have in the same formula.

  Example of interchangeable effects:

  list( list( "x1", "log_x1" ), "x2", "x3" )

• random_effects: The random effects structure. (Character)

  Is appended to the model formulas.

• max_fixed_effects: Maximum number of fixed effects in a model formula. (Integer)

  Max. limit of 5 when interactions are included !

• max_interaction_size: Maximum number of effects in an interaction. (Integer)

  Max. limit of 3.

  Use this to limit the n-way interactions allowed. 0 or 1 excludes interactions all together.

  A model formula can contain multiple interactions.

• max_effect_frequency: Maximum number of times an effect is included in a formula string.

Returns

list of model formulas.

E.g.:

c("y ~ x1 + (1|z)", "y ~ x2 + (1|z)", "y ~ x1 + x2 + (1|z)", "y ~ x1 *x2 + (1|z)").

Examples

# Attach packages
library(cvms)

# Create effect names
dependent <- "y"
fixed_effects <- c("a", "b", "c")
random_effects <- "(1|e)"

# Create model formulas
combine_predictors(
  dependent, fixed_effects,
  random_effects
)

# Create effect names with interchangeable effects in sublists
fixed_effects <- list("a", list("b", "log_b"), "c")

# Create model formulas
combine_predictors(
  dependent, fixed_effects,
  random_effects
)

Author(s)

Ludvig Renbo Olsen, r-pkgs@ludvigolsen.dk