Predict multiple future biomarker values from fitted sub-models

Internal multi-biomarker engine behind predictLongitudinal – call predictLongitudinal() directly instead (it dispatches here automatically when bio_i names more than one biomarker, or is left NULL).

Batch counterpart to dynamicPredictionBio: predicts every requested biomarker in bio_i from the same fitted longitudinal/survival sub-models and the same data_predict_all, but computes the bio_i-independent part of the pipeline (restricting to at-risk patients, the survival-side integration grid, and the denominator conditional density – see compute_bio_shared_step()) only once and reuses it across every biomarker, instead of recomputing it once per biomarker the way calling dynamicPredictionBio() in a loop would. This matters most under the Gaussian-copula path (see longitudinalSubCopula), where that denominator involves mvtnorm::pmvnorm() Monte-Carlo evaluations that are otherwise the dominant cost of a multi-biomarker prediction run.

bandcount2 (controlling the shared survival-integration grid) and bandcount3 (controlling each biomarker's own candidate-value grid) are auto-tuned separately when left at their default "auto": if bandcount2 = "auto", it is resolved once, using a single representative biomarker (the first one in bio_i), via the same doubling-until-stable check dynamicPredictionBio uses; the shared step is then built once at that resolved value. If bandcount3 = "auto", it is then resolved independently for every biomarker in bio_i (their candidate-value grids need not converge at the same resolution), reusing the once-computed shared step for every doubling round rather than rebuilding it – except for any ordinal biomarker, for which bandcount3 tuning is always skipped (its candidate grid is fixed at its category count; see dynamicPredictionBio) and "bandcount3" is recorded as NA for that biomarker. See Details in dynamicPredictionBio for the general auto-bandcount rationale.

Usage

dynamicPredictionBioAll(
  bio_i = NULL,
  data_predict_all,
  long_fit_all,
  survival_fit_all,
  prediction_time,
  horizon,
  time_variable,
  survival_variable_all,
  survival_trans_function,
  bandcount2 = "auto",
  bandcount3 = "auto"
)

Arguments

bio_i: Integer vector of biomarkers to predict. May include continuous and/or ordinal biomarkers (see dynamicPredictionBio). Defaults to NULL, meaning every biomarker in long_fit_all.
data_predict_all: See dynamicPredictionBio.
long_fit_all: See dynamicPredictionBio.
survival_fit_all: See dynamicPredictionBio.
prediction_time: See dynamicPredictionBio.
horizon: See dynamicPredictionBio.
time_variable: See dynamicPredictionBio.
survival_variable_all: See dynamicPredictionBio.
survival_trans_function: See dynamicPredictionBio.
bandcount2: See dynamicPredictionBio.
bandcount3: See dynamicPredictionBio.

Value

A named list of "predictLongitudinal.BJM" objects (see dynamicPredictionBio), one per requested biomarker, named by that biomarker's response-variable name; with attributes "bandcount2" (the single resolved/used bandcount2) and "bandcount3" (a named numeric vector of the resolved/used bandcount3 for each biomarker, or NA for an ordinal biomarker). Classed "predictLongitudinalAll.BJM".