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Validate nmar_result structure

Source: R/S3_nmar_result_validator.R
validate_nmar_result.Rd

Ensures both the child class and the parent schema are satisfied. The validator also back-fills defaults so downstream code can rely on the presence of optional components without defensive checks.

Usage

validate_nmar_result(x, class_name)

Details

This helper is the single authority on the `nmar_result` schema. It expects a list that already carries class c(class_name, "nmar_result") and at least a primary estimate stored in y_hat. All other components are optional; when they are NULL or missing, the validator supplies safe defaults:

  • Core scalars: se (numeric, default NA_real_), estimate_name (character, default NA_character_), converged (logical, default NA).

  • model: list with coefficients and vcov, both defaulting to NULL.

  • weights_info: list with values (default NULL) and trimmed_fraction (default NA_real_).

  • sample: list with n_total, n_respondents, is_survey, and design, defaulted to missing/empty values.

  • inference: list with variance_method, df, and message, all defaulted to missing values.

  • diagnostics, meta, and extra: defaulted to empty lists, with meta carrying engine_name, call, and formula when unset.

Engine constructors should normally call new_nmar_result() rather than invoking this function directly. new_nmar_result() attaches classes and funnels all objects through validate_nmar_result() so downstream S3 methods can assume a consistent structure.