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Performs Cox Proportional Hazards regression using the omnibus function

Source: R/Cox_Regression.R
RunCoxRegression_Omnibus.Rd

RunCoxRegression_Omnibus uses user provided data, time/event columns, vectors specifying the model, and options to control the convergence and starting positions. Has additional options for starting with several initial guesses, using stratification, multiplicative loglinear 1-term, competing risks, and calculation without derivatives

Usage

RunCoxRegression_Omnibus(
  df,
  time1 = "start",
  time2 = "end",
  event0 = "event",
  names = c("CONST"),
  term_n = c(0),
  tform = "loglin",
  keep_constant = c(0),
  a_n = c(0),
  modelform = "M",
  fir = 0,
  der_iden = 0,
  control = list(),
  strat_col = "null",
  cens_weight = "null",
  model_control = list(),
  cons_mat = as.matrix(c(0)),
  cons_vec = c(0)
)

Arguments

df

a data.table containing the columns of interest

time1

column used for time period starts

time2

column used for time period end

event0

column used for event status

names

columns for elements of the model, used to identify data columns

term_n

term numbers for each element of the model

tform

list of string function identifiers, used for linear/step

keep_constant

binary values to denote which parameters to change

a_n

list of initial parameter values, used to determine number of parameters. May be either a list of vectors or a single vector.

modelform

string specifying the model type: M, ME, A, PA, PAE, GMIX, GMIX-R, GMIX-E

fir

term number for the initial term, used for models of the form T0*f(Ti) in which the order matters

der_iden

number for the subterm to test derivative at, only used for testing runs with a single varying parameter, should be smaller than total number of parameters. indexed starting at 0

control

list of parameters controlling the convergence, see Def_Control() for options or vignette("Control_Options")

strat_col

column to stratify by if needed

cens_weight

column containing the row weights

model_control

controls which alternative model options are used, see Def_model_control() for options and vignette("Control_Options") for further details

cons_mat

Matrix containing coefficients for system of linear constraints, formatted as matrix

cons_vec

Vector containing constants for system of linear constraints, formatted as vector

Value

returns a list of the final results

See also

Other Cox Wrapper Functions: RunCoxNull(), RunCoxRegression(), RunCoxRegression_Basic(), RunCoxRegression_CR(), RunCoxRegression_Guesses_CPP(), RunCoxRegression_Omnibus_Multidose(), RunCoxRegression_Single(), RunCoxRegression_Strata(), RunCoxRegression_Tier_Guesses()

Examples

library(data.table)
## basic example code reproduced from the starting-description vignette
df <- data.table::data.table(
  "UserID" = c(112, 114, 213, 214, 115, 116, 117),
  "Starting_Age" = c(18, 20, 18, 19, 21, 20, 18),
  "Ending_Age" = c(30, 45, 57, 47, 36, 60, 55),
  "Cancer_Status" = c(0, 0, 1, 0, 1, 0, 0),
  "a" = c(0, 1, 1, 0, 1, 0, 1),
  "b" = c(1, 1.1, 2.1, 2, 0.1, 1, 0.2),
  "c" = c(10, 11, 10, 11, 12, 9, 11),
  "d" = c(0, 0, 0, 1, 1, 1, 1),
  "e" = c(0, 0, 1, 0, 0, 0, 1)
)
# For the interval case
time1 <- "Starting_Age"
time2 <- "Ending_Age"
event <- "Cancer_Status"
names <- c("a", "b", "c", "d")
a_n <- list(c(1.1, -0.1, 0.2, 0.5), c(1.6, -0.12, 0.3, 0.4))
# used to test at a specific point
term_n <- c(0, 1, 1, 2)
tform <- c("loglin", "lin", "lin", "plin")
modelform <- "M"
fir <- 0
keep_constant <- c(0, 0, 0, 0)
der_iden <- 0
control <- list(
  "ncores" = 2, "lr" = 0.75, "maxiters" = c(5, 5, 5),
  "halfmax" = 5, "epsilon" = 1e-3, "deriv_epsilon" = 1e-3,
  "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0,
  "verbose" = FALSE,
  "ties" = "breslow", "double_step" = 1, "guesses" = 2
)
e <- RunCoxRegression_Omnibus(df, time1, time2, event,
  names, term_n, tform, keep_constant,
  a_n, modelform, fir, der_iden, control,
  model_control = list(
    "single" = FALSE,
    "basic" = FALSE, "cr" = FALSE, "null" = FALSE
  )
)