RunPoissonRegression_Joint_Omnibus: Performs joint Poisson regression using the omnibus function

In Colossus: "Risk Model Regression and Analysis with Complex Non-Linear Models"

Performs joint Poisson regression using the omnibus function

Description

RunPoissonRegression_Joint_Omnibus uses user provided data, time/event columns, vectors specifying the model, and options to control the convergence and starting positions. Has additional options to starting with several initial guesses, uses joint competing risks equation

Usage

RunPoissonRegression_Joint_Omnibus(
  df,
  pyr0,
  events,
  name_list,
  term_n_list = list(),
  tform_list = list(),
  keep_constant_list = list(),
  a_n_list = list(),
  modelform = "M",
  control = list(),
  strat_col = "null",
  model_control = list(),
  cons_mat = as.matrix(c(0)),
  cons_vec = c(0)
)

Arguments

df	a data.table containing the columns of interest
pyr0	column used for person-years per row
events	vector of event column names
name_list	list of vectors for columns for event specific or shared model elements, required
term_n_list	list of vectors for term numbers for event specific or shared model elements, defaults to term 0
tform_list	list of vectors for subterm types for event specific or shared model elements, defaults to loglinear
keep_constant_list	list of vectors for constant elements for event specific or shared model elements, defaults to free (0)
a_n_list	list of vectors for parameter values for event specific or shared model elements, defaults to term 0
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
cons_mat	Matrix containing coefficients for a system of linear constraints, formatted as matrix
cons_vec	Vector containing constants for a system of linear constraints, formatted as vector

Value

returns a list of the final results

See Also

Other Poisson Wrapper Functions: PoissonCurveSolver(), RunPoissonEventAssignment(), RunPoissonEventAssignment_bound(), RunPoissonRegression(), RunPoissonRegression_Guesses_CPP(), RunPoissonRegression_Omnibus(), RunPoissonRegression_Residual(), RunPoissonRegression_Single(), RunPoissonRegression_Strata(), RunPoissonRegression_Tier_Guesses()

Examples

library(data.table)
## basic example code reproduced from the starting-description vignette
a <- c(0, 0, 0, 1, 1, 1)
b <- c(1, 1, 1, 2, 2, 2)
c <- c(0, 1, 2, 2, 1, 0)
d <- c(1, 1, 0, 0, 1, 1)
e <- c(0, 1, 1, 1, 0, 0)
f <- c(0, 1, 0, 0, 1, 1)
df <- data.table("t0" = a, "t1" = b, "e0" = c, "e1" = d, "fac" = e)
time1 <- "t0"
time2 <- "t1"
df$pyr <- df$t1 - df$t0
pyr <- "pyr"
events <- c("e0", "e1")
names_e0 <- c("fac")
names_e1 <- c("fac")
names_shared <- c("t0", "t0")
term_n_e0 <- c(0)
term_n_e1 <- c(0)
term_n_shared <- c(0, 0)
tform_e0 <- c("loglin")
tform_e1 <- c("loglin")
tform_shared <- c("quad_slope", "loglin_top")
keep_constant_e0 <- c(0)
keep_constant_e1 <- c(0)
keep_constant_shared <- c(0, 0)
a_n_e0 <- c(-0.1)
a_n_e1 <- c(0.1)
a_n_shared <- c(0.001, -0.02)
name_list <- list("shared" = names_shared, "e0" = names_e0, "e1" = names_e1)
term_n_list <- list("shared" = term_n_shared, "e0" = term_n_e0, "e1" = term_n_e1)
tform_list <- list("shared" = tform_shared, "e0" = tform_e0, "e1" = tform_e1)
keep_constant_list <- list(
  "shared" = keep_constant_shared,
  "e0" = keep_constant_e0, "e1" = keep_constant_e1
)
a_n_list <- list("shared" = a_n_shared, "e0" = a_n_e0, "e1" = a_n_e1)
modelform <- "M"
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,
  "ties" = "breslow", "double_step" = 1
)
guesses_control <- list(
  "maxiter" = 10, "guesses" = 10,
  "lin_min" = 0.001, "lin_max" = 1,
  "loglin_min" = -1, "loglin_max" = 1, "lin_method" = "uniform",
  "loglin_method" = "uniform", strata = FALSE
)
strat_col <- "f"
e <- RunPoissonRegression_Joint_Omnibus(
  df, pyr, events, name_list,
  term_n_list,
  tform_list, keep_constant_list,
  a_n_list,
  modelform,
  control, strat_col
)

Colossus documentation built on June 8, 2025, 1:10 p.m.