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Build model matrices from a parsed formula

Source: R/formula.R
tulpa_build_model_data.Rd

Takes a parsed formula and data frame, and constructs:

  • The fixed-effects design matrix X

  • An offset vector (or NULL) extracted from offset(...) terms

  • RE group index vectors

  • RE slope matrices (if applicable)

Usage

tulpa_build_model_data(parsed, data)

Arguments

parsed

A tulpa_parsed_formula object

data

A data frame

Value

A list with:

  • y: response vector (or NULL). A cbind(successes, failures) response is resolved to the successes column.

  • n_trials: binomial denominators when the response was written as cbind(successes, failures), otherwise NULL

  • X: fixed-effects design matrix

  • offset: numeric vector or NULL

  • re_terms: list of RE data structures (group indices, slope matrices)

Details

Missing values pass through (na.action = na.pass), because a prior predictive may have no response; the fitting doors refuse them. Unused levels of a grouping factor are dropped, so n_groups counts the groups that have data.

Examples

d <- data.frame(y = rnorm(6), x = 1:6, g = rep(1:2, 3))
parsed <- tulpa_parse_formula(y ~ x + (1 | g))
md <- tulpa_build_model_data(parsed, d)
dim(md$X)
md$n_re_terms