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Internal helper for the part of dynamicPredictionBio()'s pipeline that does depend on which biomarker is being predicted: building the candidate-value grid Y_all, evaluating the numerator conditional density on it, and assembling/normalizing Y_density and Y_predict. Takes the output of compute_bio_shared_step() so the bio_i-independent pieces are not recomputed.

Usage

compute_bio_marker_step(
  shared,
  bio_i,
  long_fit_all,
  survival_fit_all,
  prediction_time,
  horizon,
  time_variable,
  survival_variable_all,
  survival_trans_function,
  bandcount3
)

Arguments

shared

Output of compute_bio_shared_step().

bio_i

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.

bandcount3

See dynamicPredictionBio.

Value

A list with Y_predict, Y_density, Y_all (matching dynamicPredictionBio()'s return value fields). For an ordinal bio_i, Y_all/Y_predict hold integer category codes (1:K, in threshold order) rather than a numeric grid – see Details below – and Y_all additionally carries a "category_labels" attribute with the matching level-label strings.