RunCoxPlots {Colossus} | R Documentation |
Performs Cox Proportional Hazard model plots
Description
RunCoxPlots
uses user provided data, time/event columns,
vectors specifying the model, and options to choose and save plots
Usage
RunCoxPlots(
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,
control = list(),
plot_options = list(),
model_control = list()
)
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") |
plot_options |
list of parameters controlling the plot options, see RunCoxPlots() for different options |
model_control |
controls which alternative model options are used, see Def_model_control() for options and vignette("Control_Options") for further details |
Value
saves the plots in the current directory and returns a string
See Also
Other Plotting Wrapper Functions:
Cox_Relative_Risk()
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(-0.1, 0.5, 1.1, -0.3)
keep_constant <- c(0, 0, 0, 0)
der_iden <- 0
control <- list(
"ncores" = 2, "lr" = 0.75, "maxiter" = -1, "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
)
# setting maxiter below 0 forces the function to calculate the score
# and return
plot_options <- list(
"type" = c("surv", paste(tempfile(),
"run",
sep = ""
)), "studyid" = "UserID",
"verbose" = FALSE
)
RunCoxPlots(
df, time1, time2, event, names, term_n, tform, keep_constant,
a_n, modelform, fir, control, plot_options
)