ic_pred_cache: Build the subject-by-interval prediction grid used for IC...

In pammtools: Piece-Wise Exponential Additive Mixed Modeling Tools for Survival Analysis

Build the subject-by-interval prediction grid used for IC imputation

Description

Constructs the (subjects \times intervals) grid on the fixed cut-points and evaluates the lpmatrix of the fitted PAMM once, so that across imputations only the linear predictor (and hence the hazard) needs to be recomputed for a new coefficient draw. Rows are subject-major: the first n_int rows belong to subject 1, the next n_int to subject 2, etc., so that matrix(h, nrow = n_int) has one column per subject.

Usage

ic_pred_cache(object, ic, cut, cause_levels = NULL, cause_var = "cause")

Arguments

object	A fitted pamm model used as imputation model.
ic	A data frame as returned by parse_ic_surv (subject- level, with covariates and ic_L/ic_R/ic_kind).
cut	The fixed vector of interval cut-points (shared across imputations).
cause_levels	Optional character vector of competing-risk cause levels. When supplied, one lpmatrix per cause is built and returned in X_list.
cause_var	Name of the cause column expected by the model.

Value

A list with the interval information ii, n_int, n_sub, and either a single design matrix X or a list X_list (competing risks).

pammtools documentation built on Aug. 27, 2026, 1:08 a.m.