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Parse a single random effect bar term

Source: R/formula.R
parse_bar_term.Rd

Takes a | or || language object and extracts the grouping variable(s), effect terms (intercept, slopes), and correlation structure. The bar operator drives the correlated flag: | -> TRUE (LKJ-Cholesky on the joint slope vector), || -> FALSE (diagonal covariance, one sigma per coefficient). This matches lme4 / glmmTMB and lets downstream packages branch on correlated to choose between independent-sigma and Cholesky parameterizations.

Usage

parse_bar_term(bar_term)

Arguments

bar_term

A language object: |(lhs, rhs) or ||(lhs, rhs)

Value

A list of RE specs (one per grouping level). Each spec has:

  • group_var: character, display label (colon-joined for nested)

  • group_vars: character vector, each element a column name

  • group_expr: language or NULL (set when grouping is a non-name expr)

  • slope_terms: list of language objects (slope LHS terms)

  • has_intercept: logical

  • correlated: logical (TRUE for |, FALSE for ||)

  • original: the original bar language object

Details

Nested grouping (1 | a/b) is expanded into one spec per level (a, then a:b). || is preserved as a single spec rather than split into multiple | bars, so the original user intent (one logical RE term with diagonal covariance) round-trips through the parsed object.