GHRmodel (version 0.1.1)

cov_interact: Generate Interaction Terms Between Covariates

Description

This function generates interaction terms between covariates specified in the pattern or name arguments. It requires a list of character vectors and appends interaction terms to each vector based on pairwise or three-way interactions. The resulting list can be input into the covariates argument in write_inla_formulas.

Usage

cov_interact(covariates = NULL, pattern = NULL, name = NULL, add = FALSE)

Value

A list of character vectors, where each vector includes covariates and their corresponding interaction terms. This object can be passed to the covariates argument in write_inla_formulas.

Arguments

covariates

A list of character vectors, each vector containing variable names. Typically an output of cov_multi or cov_uni.

pattern

A character vector of length 2 or 3 specifying prefixes of variables to interact (e.g., "tmin" matches "tmin", "tmin.l1", etc.).

name

A character vector specifying the exact variable names to be included in the interactions.

add

Logical; if TRUE, appends the newly created formulas to the original list. Default is FALSE.

Details

• If two variables are matched, their pairwise interaction is added (var1:var2).

• If three variables are matched, two-way and three-way interactions are generated.

• Only variables that are expressed as linear terms can be used in interactions.

• Use either pattern, name, or both to identify variables for interaction.

Examples

# Example dataset
data <- data.frame(tmin.l1 = rnorm(10), pdsi.l1 = rnorm(10), urban = rnorm(10))

# Extract names
covs <- extract_names(data, pattern = c("tmin", "pdsi", "urban"))

# Create combinations
combos <- cov_multi(covariates = covs, pattern = c("tmin", "pdsi"))

# Add interaction terms
cov_interact(covariates = combos, pattern = c("tmin", "pdsi"))

# Output can be passed to write_inla_formulas()
new_covs <- cov_interact(combos, pattern = c("tmin", "pdsi"))
formulas <- write_inla_formulas(outcome = "cases", covariates = new_covs)