Parse a formula (and possibly subformulas)
find_modfr_glmm(formula, subformula = NULL, data = NULL,
family = gaussian, weights = NULL, offset = NULL,
lme4_control = set_lme4_control())a two-sided linear formula object describing both the
fixed-effects and random-effects part of the model, with the response
on the left of a ~ operator and the terms, separated by
+ operators, on the right. Random-effects terms are
distinguished by vertical bars ("|") separating expressions
for design matrices from grouping factors.
a subformula, describing how a substituted variable
depends on covariates, or a list of subformulas, if there is more
than one Sub() term in formula.
an optional data frame, list or environment containing the
variables named in formula, and in any of the subformulas.
an optional vector of ‘prior weights’ to be used
in the fitting process. Should be NULL or a numeric
vector.
this can be used to specify an a priori known
component to be included in the linear predictor during
fitting. This should be NULL or a numeric vector of length
equal to the number of cases. One or more offset
terms can be included in the formula instead or as well, and if more
than one is specified their sum is used. See model.offset.
the result of a call to lme4_control, containing
control parameters passed to lme4. See ?lme4_control.