Skip to contents

Predicts how many events are due to baseline vs excess

Source: R/Poisson_Regression.R
RunPoissonEventAssignment.Rd

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 the Control_Options vignette for details

strat_col

column to stratify by if needed

model_control

controls which alternative model options are used, see the Control_Options vignette for further details

Value

returns a list of the final results

See also

Other Poisson Wrapper Functions: EventAssignment.poisres(), LikelihoodBound.poisres(), PoisRun(), PoisRunJoint(), PoisRunMulti(), PoissonCurveSolver(), Residual.poisres(), RunPoisRegression_Omnibus_Multidose(), RunPoissonEventAssignment_bound(), RunPoissonRegression_Joint_Omnibus(), RunPoissonRegression_Omnibus(), RunPoissonRegression_Residual()