Package 'WinsCRT'

Example prioritized event-log dataset

Description

dat is an example longitudinal event-log dataset for demonstrating WinsCRT().

Usage

data(dat)

Format

A data frame with columns clu, id, trt, t, st.

Details

Status coding convention:

• st = 0: censoring / terminal no event

• positive integers denote event types

• larger positive value indicates higher priority

Columns:

• clu: cluster ID

• id: subject ID within cluster

• trt: cluster treatment indicator (0/1)

• t: event/censoring time

• st: event status / priority code

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WinsCRT: Win-statistics inference for CRT prioritized event logs

Description

Computes one requested estimand and performs inference using one requested method. Input must be longitudinal event-log data with cluster-level treatment.

Status convention:

• status = 0 means censor/no event

• for positive statuses, larger value means higher priority (smaller value means lower priority)

Usage

WinsCRT(
  data,
  cluster,
  subject,
  trt,
  time,
  status,
  method = c("wald_score", "wald_u", "wald_jk", "perm", "fs", "jel"),
  estimand = c("WD", "WR", "WO", "DOOR"),
  null = NULL,
  alternative = c("two.sided", "greater", "less"),
  alpha = 0.05,
  use_t = TRUE,
  B = 2000L,
  seed = NULL,
  keep = NULL,
  strict = TRUE
)

Arguments

data	data.frame in long event-log format.
cluster	character: cluster id column.
subject	character: subject id column.
trt	character: treatment column (0/1), constant within cluster.
time	character: event/censoring time column (numeric).
status	character: status/priority column (integer >=0).
method	one of "wald_score","wald_u","wald_jk","perm","fs","jel".
estimand	one of "WD","WR","WO","DOOR".
null	optional null value; default is canonical by estimand.
alternative	"two.sided","greater","less" where applicable.
alpha	confidence level is 1-alpha (default 0.05).
use_t	logical; t-reference where implemented.
B	integer; resamples for perm and optional fs randomization p-value.
seed	optional integer seed.
keep	optional vector of cluster IDs to include.
strict	logical passed to C++ kernels.

Value

Object of class "WinsCRT".

Examples

ex_dat <- data.frame(
  clu = rep(1:4, each = 2),
  id = rep(1:2, times = 4),
  trt = rep(c(0, 0, 1, 1), each = 2),
  t = c(5, 4, 6, 7, 6, 5, 7, 8),
  st = c(0, 1, 0, 1, 0, 1, 0, 1)
)

fit <- WinsCRT(
  data = ex_dat,
  cluster = "clu",
  subject = "id",
  trt = "trt",
  time = "t",
  status = "st",
  method = "perm",
  estimand = "WD",
  B = 19L,
  seed = 1
)
fit
summary(fit)

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