| RunCoxRegression_Basic {Colossus} | R Documentation |
Performs basic Cox Proportional Hazards regression with a multiplicative log-linear model
Description
RunCoxRegression_Basic uses user provided data, time/event columns, vectors specifying the model, and options to control the convergence and starting positions
Usage
RunCoxRegression_Basic(
df,
time1,
time2,
event0,
names,
keep_constant,
a_n,
der_iden,
control
)
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 |
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 |
control |
list of parameters controlling the convergence, see Def_Control() for options or vignette("starting_description") |
Value
returns a list of the final results
See Also
Other Cox Wrapper Functions:
RunCoxEventAssignment(),
RunCoxNull(),
RunCoxRegression(),
RunCoxRegression_CR(),
RunCoxRegression_Guesses_CPP(),
RunCoxRegression_Omnibus(),
RunCoxRegression_STRATA(),
RunCoxRegression_Single(),
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,'dbeta_max' = 0.5,'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)