RunPoissonEventAssignment {Colossus} | R Documentation |
Predicts how many events are due to baseline vs excess
Description
RunPoissonEventAssignment
uses user provided data, person-year/event columns, vectors specifying the model, and options to calculate background and excess events
Usage
RunPoissonEventAssignment(
df,
pyr0 = "pyr",
event0 = "event",
names = c("CONST"),
term_n = c(0),
tform = "loglin",
keep_constant = c(0),
a_n = c(0),
modelform = "M",
control = list(),
strat_col = "null",
model_control = list()
)
Arguments
df |
a data.table containing the columns of interest |
pyr0 |
column used for person-years per row |
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 the 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 |
control |
list of parameters controlling the convergence, see Def_Control() for options or vignette("Control_Options") |
strat_col |
column to stratify by if needed |
model_control |
controls which alternative model options are used, see Def_model_control() for options and vignette("Control_Options") for further details |
Value
returns a list of the final results
See Also
Other Poisson Wrapper Functions:
PoissonCurveSolver()
,
RunPoissonEventAssignment_bound()
,
RunPoissonRegression()
,
RunPoissonRegression_Guesses_CPP()
,
RunPoissonRegression_Joint_Omnibus()
,
RunPoissonRegression_Omnibus()
,
RunPoissonRegression_Residual()
,
RunPoissonRegression_Single()
,
RunPoissonRegression_Strata()
,
RunPoissonRegression_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
df$pyr <- df$Ending_Age - df$Starting_Age
pyr <- "pyr"
event <- "Cancer_Status"
names <- c("a", "b", "c", "d")
term_n <- c(0, 1, 1, 2)
tform <- c("loglin", "lin", "lin", "plin")
modelform <- "M"
a_n <- c(0.1, 0.1, 0.1, 0.1)
keep_constant <- c(0, 0, 0, 0)
control <- list(
"ncores" = 2, "lr" = 0.75, "maxiter" = 5,
"halfmax" = 5, "epsilon" = 1e-3,
"deriv_epsilon" = 1e-3, "abs_max" = 1.0,
"dose_abs_max" = 100.0, "verbose" = FALSE, "double_step" = 1
)
e <- RunPoissonEventAssignment(
df, pyr, event, names, term_n,
tform, keep_constant,
a_n, modelform, control
)