Performs basic Cox Proportional Hazards regression with a multiplicative log-linear model
Source:R/Cox_Regression.R
RunCoxRegression_Basic.Rd
RunCoxRegression_Basic
uses user provided data, time/event columns, vectors specifying the model, and options to control the convergence and starting positions
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
- 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.
- 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")
See also
Other Cox Wrapper Functions:
RunCoxNull()
,
RunCoxRegression()
,
RunCoxRegression_CR()
,
RunCoxRegression_Guesses_CPP()
,
RunCoxRegression_Omnibus()
,
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)
)
# For the interval case
time1 <- "Starting_Age"
time2 <- "Ending_Age"
event <- "Cancer_Status"
names <- c("a", "b", "c", "d")
a_n <- c(1.1, -0.1, 0.2, 0.5) # used to test at a specific point
keep_constant <- c(0, 0, 0, 0)
der_iden <- 0
control <- list(
"ncores" = 2, "lr" = 0.75, "maxiter" = 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
)
e <- RunCoxRegression_Basic(
df, time1, time2, event, names, keep_constant,
a_n, der_iden, control
)