Parses the two-part Formula, constructs EL design matrices, injects the respondent delta indicator, attaches weights and survey metadata, and returns the pieces needed by the EL core.
el_prepare_inputs(
formula,
data,
weights = NULL,
n_total = NULL,
design_object = NULL
)Enforeces the following format required by the rest of el code:
LHS references exactly one outcome source variable in data; any
transforms are applied via the formula environment and must be defined
for all respondent rows.
The outcome is never allowed to appear on RHS1 (auxiliaries) or RHS2
(missingness predictors), either explicitly in the formula or implicitly
via dot (.) expansion. The missingness model uses the evaluated LHS
expression as a dedicated predictor column instead.
RHS1 always yields an intercept-free auxiliary design matrix with
k-1 coding for factor auxiliaries, regardless of user +0/-1 syntax or
custom contrasts. Auxiliary columns are validated to be fully observed
and non-constant among respondents.
RHS2 always yields a missingness-design matrix for respondents that includes an intercept column and zero-variance predictors emit warnings. NA among respondents is rejected.
respondent_mask is defined from the raw outcome in data, not from
the transformed LHS. An injected ..nmar_delta.. indicator in
analysis_data must match this mask.
N_pop is the analysis-scale population size:
for IID it is nrow(data) unless overridden by n_total.
For survey designs it is sum(weights) or n_total when supplied.