ciftest: Tests for survival and cumulative incidence curves

In cifmodeling: Visualization and Polytomous Modeling of Survival and Competing Risks

Tests for survival and cumulative incidence curves

Description

Provides a formula-based interface for log-rank, Fleming-Harrington, Gray, and augmented score tests. test = "auto" selects log-rank for survival outcomes and the augmented score test for competing-risk outcomes. The "early" and "late" presets select that same outcome-specific test with Fleming–Harrington parameters ⁠(rho, gamma) = (1, 0)⁠ and ⁠(0, 1)⁠, respectively. Analysis strata can be specified independently with strata. For augmented tests, working Aalen-Johansen distributions are estimated within exposure-by-strata.competing.risk cells, censoring distributions are estimated within strata.censor, and the closed-form augmentation is used. Setting iteration to a positive integer applies that many Scheike fixed-point refinements. Finite iterates are anchored as the closed-form score plus the change in the AIPWCC image from the seed to the refined direction, preserving the zeroth-step identity in the observed sample.

Usage

ciftest(
  formula,
  data,
  weights = NULL,
  subset.condition = NULL,
  na.action = na.omit,
  outcome.type = "auto",
  test = "auto",
  code.event1 = 1,
  code.event2 = 2,
  code.censoring = 0,
  rho = NULL,
  gamma = NULL,
  iteration = 0L,
  tolerance = NULL,
  strata = NULL,
  strata.censor = NULL,
  strata.competing.risk = NULL,
  tau = NULL,
  prob.bound = 1e-07,
  prob.truncation = NULL,
  ...
)

Arguments

formula	A two-sided formula with an Event() or Surv() response and one grouping variable on the right-hand side. Surv() responses must be right-censored.
data	A data frame containing variables in the formula.
weights	Optional numeric case weights or the name of a weight column. The standard Gray branch currently accepts integer frequency weights.
subset.condition	Optional character string giving a logical condition to subset data (default NULL).
na.action	A function specifying the action to take on missing values (default na.omit).
outcome.type	One of "auto", "competing-risk", or "survival". The aliases "C" and "S" are accepted.
test	One of "auto", "early", "late", "logrank", "gray", "score", "augmented", or "multiple". The aliases "L", "LR", and "log-rank" select log-rank; "G" selects Gray; and "A", "aug", and "augmentation" select the augmented score test. The early and late choices are outcome-specific single-direction presets. "multiple" (aliases "multi" and "m") returns ciftest_mdir() using the default directions ⁠(rho, gamma) = (2, 0), (0, 2), (0, 0)⁠. "score" uses the null score-IID variance; for competing-risk outcomes it may use censoring Kaplan–Meier strata.
code.event1	Integer code of the event of interest (default 1).
code.event2	Integer code of the competing risk (default 2).
code.censoring	Integer code of censoring (default 0).
rho, gamma	Optional non-negative Fleming-Harrington weight parameters. Omitted values default to zero. They cannot be combined with the fixed "early" and "late" presets.
iteration	Non-negative integer giving the number of Scheike fixed-point refinements. 0 returns the closed-form augmented score; positive values use the closed-form-anchored AIPWCC difference.
tolerance	Optional positive convergence tolerance. NULL performs exactly the requested number of finite iterations.
strata	Optional character vector of one or more column names defining analysis strata. Multiple columns define their observed interaction. The grouping variable cannot be included. Event risk sets, null event distributions, and Fleming–Harrington weight processes are constructed separately within these strata, and their score vectors are summed. This is distinct from the two nuisance-model strata.
strata.censor	Optional character vector of one or more column names defining censoring Kaplan-Meier strata. The grouping variable may be included explicitly when group-specific censoring distributions are required.
strata.competing.risk	Optional character vector of one or more column names defining the exposure-by-stratum working Aalen-Johansen models used for the competing-risk nuisance distribution. The grouping variable must not be included because it is crossed with these strata automatically.
tau	Optional finite non-negative analysis horizon.
prob.bound	Strictly positive numerical/positivity bound. Required nuisance probabilities at or below this value produce an error rather than being silently replaced.
prob.truncation	Optional probability lower truncation strictly above prob.bound. It is applied only to positive censoring and working-survival denominators used by score and augmented tests.
...	Reserved for future extensions.

Value

An object inheriting from "ciftest" and "htest", with a test-specific subclass. An ordinary unweighted log-rank result also inherits from "survdiff" and contains a fully compatible object in survdiff. Every score-based branch returns an analysis-row by contrast matrix of individual null-score contributions in score.iid. Augmented results include score.iid.base, score.iid.censor, and score.iid.augment matrices and use their summed empirical cross-product as vcov.score. Standard Gray results retain the classical Gray covariance. If the optional standard-Gray score-IID diagnostic cannot be constructed, the Gray test is still returned; its score-IID matrices contain NA and the reason is recorded in diagnostics$score.iid.error. Positive iteration values return the requested finite-iteration score, its subject-level score matrix, anchoring diagnostics, and fixed-point diagnostics. The event-time FH process actually used by the fit is returned in diagnostics$fh.weight.process, including whether it came from the pooled or event-stratified AJ left limit or the native Gray subdistribution construction.

cifmodeling documentation built on Nov. 11, 2026, 9:06 a.m.