ezcox_parallel: Parallelly Run Cox Analysis in Batch Mode

In ezcox: Easily Process a Batch of Cox Models

Parallelly Run Cox Analysis in Batch Mode

Description

Parallelly Run Cox Analysis in Batch Mode

Usage

ezcox_parallel(
  data,
  covariates,
  controls = NULL,
  time = "time",
  status = "status",
  batch_size = 100,
  global_method = c("likelihood", "wald", "logrank"),
  keep_models = FALSE,
  return_models = FALSE,
  model_dir = file.path(tempdir(), "ezcox"),
  parallel = TRUE,
  verbose = FALSE
)

Arguments

data	a data.frame containing variables, time and os status.
covariates	column names specifying variables.
controls	column names specifying controls.
time	column name specifying time, default is 'time'.
status	column name specifying event status, default is 'status'.
batch_size	processing size in a batch.
global_method	method used to obtain global p value for cox model, should be one of "likelihood", "wald", "logrank". The likelihood-ratio test, Wald test, and score logrank statistics. These three methods are asymptotically equivalent. For large enough N, they will give similar results. For small N, they may differ somewhat. The Likelihood ratio test has better behavior for small sample sizes, so it is generally preferred.
keep_models	If TRUE, keep models as local files.
return_models	default FALSE. If TRUE, return a list contains cox models.
model_dir	a path for storing model results.
parallel	if TRUE, do parallel computation by furrr package.
verbose	if TRUE, print extra info. If parallel is TRUE, set verbose to FALSE may speed up.

Value

a ezcox object

Author(s)

Shixiang Wang [e-mail]

Examples

library(survival)
t <- ezcox_parallel(lung, covariates = c("sex", "ph.ecog"), controls = "age")
t

ezcox documentation built on May 31, 2023, 7:49 p.m.