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Aggregate Posterior Profile Draws into R_ALL / R_KNOWN_OUTCOME / R_NF Summaries

Source: R/daly_resistance_profiles.R
aggregate_profiles_for_daly.Rd

Summarises draw-level R_ALL, R_KNOWN_OUTCOME, and R_NF values from compute_event_profile_probabilities() into posterior mean and credible interval per hospital x pathogen x profile combination, and derives explicit eligible_for_YLL/eligible_for_YLD flags (with reasons) rather than asserting universal usability.

Usage

aggregate_profiles_for_daly(
  profile_output,
  hospital_col = "hospital",
  pathogen_col = "pathogen",
  estimand = "observed_stewardship_event_mix",
  ci_level = 0.95,
  min_n_events = 10L,
  min_n_draws = 100L,
  sampler_acceptable = TRUE
)

Arguments

profile_output

List returned by compute_event_profile_probabilities().

hospital_col

Character. Hospital column in aggregate_draws. Must match the upper RE column used during fitting. Default "hospital".

pathogen_col

Character. Pathogen column. Default "pathogen".

estimand

Character. Estimand label to attach to output. Default "observed_stewardship_event_mix".

ci_level

Numeric. Credible interval coverage. Default 0.95.

min_n_events

Integer. Minimum events in the relevant cohort (known-outcome for YLL, nonfatal for YLD) for eligibility. Default 10L.

min_n_draws

Integer. Minimum valid posterior draws in the relevant summary for eligibility. Default 100L.

sampler_acceptable

Logical, scalar or one value per row of profile_output$aggregate_draws groups. Whether the fit's sampler diagnostics are acceptable (e.g. fitted_model$diagnostics$converged_structural from fit_bayesian_multivariate_probit()); FALSE makes every row ineligible for YLL/YLD regardless of panel/count support. Default TRUE (i.e. does not gate on sampler status unless the caller supplies it – estimate_resistance_profiles() supplies it automatically).

Value

Tibble with one row per hospital x pathogen x profile: R_ALL, R_KNOWN_OUTCOME, and R_NF posterior mean and credible interval, panel composition (n_profile_classes, panel_eligibility_method, classes_excluded, classes_excluded_reason), event and draw counts, and profile/YLL/YLD eligibility flags with reasons.

Details

Cohort definitions: R_ALL is the mean over truly all events in the hospital-pathogen-panel cohort (no outcome filter). R_KNOWN_OUTCOME restricts to events with a known patient outcome (this is what earlier versions of this function called R_ALL – renamed because it is not actually all events). R_NF restricts to the non-fatal subset of the known-outcome cohort. All three are computed per posterior draw and then summarised here; n_draws_all/n_draws_known_outcome/n_draws_nf count only the non-NA draws feeding each summary (a cohort that is empty for a given hospital-pathogen pair yields NA draws, which must not be silently counted as valid support).

Eligibility: eligible_for_profile_inference is a hard boolean, TRUE only for rows generated by a conditional (observed-plus-imputed) method – "conditional_analytic_identity" or "conditional_gibbs_correlated"; see compute_event_profile_probabilities(). FALSE for any other profile_generation_method value, including the legacy "unconditional_simulation_correlated_not_daly_eligible" tag from an older profile_output – callers must not rely on the descriptive profile_generation_method string alone. eligible_for_YLL/eligible_for_YLD additionally require: sampler_acceptable (passed in by the caller, e.g. from fitted_model$diagnostics$converged_structural); the relevant event cohort has at least min_n_events events; and at least min_n_draws valid posterior draws contributed to the relevant summary. exclusion_reason_YLL/exclusion_reason_YLD record why, distinguishing a cohort that is completely empty ("no_known_outcome_events" / "no_nonfatal_events") from one that is merely small ("too_few_known_outcome_events" / "too_few_nonfatal_events").