Performs basic Cox Proportional Hazards calculation with no derivative
Source:R/Cox_Regression.R
RunCoxRegression_Single.Rd
RunCoxRegression_Single
uses user provided data, time/event columns, vectors specifying the model, and options and returns the log-likelihood
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
- 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_Basic()
,
RunCoxRegression_CR()
,
RunCoxRegression_Guesses_CPP()
,
RunCoxRegression_Omnibus()
,
RunCoxRegression_Omnibus_Multidose()
,
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")
term_n <- c(0, 1, 1, 2)
tform <- c("loglin", "lin", "lin", "plin")
modelform <- "M"
fir <- 0
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)
control <- list(
"ncores" = 2, "verbose" = FALSE,
"ties" = "breslow", "double_step" = 1
)
e <- RunCoxRegression_Single(
df, time1, time2, event, names, term_n, tform,
keep_constant, a_n, modelform, fir, control
)