Performs Poisson regression using the omnibus function with multiple column realizations
Source:R/Poisson_Regression.R
RunPoisRegression_Omnibus_Multidose.Rd
RunPoisRegression_Omnibus_Multidose
uses user provided data, time/event columns,
vectors specifying the model, and options to control the convergence
and starting positions. Used for 2DMC column uncertainty methods.
Returns optimized parameters, log-likelihood, and standard deviation for each realization.
Has additional options for using stratification
Usage
RunPoisRegression_Omnibus_Multidose(
df,
pyr0 = "pyr",
event0 = "event",
names = c("CONST"),
term_n = c(0),
tform = "loglin",
keep_constant = c(0),
a_n = c(0),
modelform = "M",
realization_columns = matrix(c("temp00", "temp01", "temp10", "temp11"), nrow = 2),
realization_index = c("temp0", "temp1"),
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
- 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
- realization_columns
used for multi-realization regressions. Matrix of column names with rows for each column with realizations, columns for each realization
- realization_index
used for multi-realization regressions. Vector of column names, one for each column with realizations. Each name should be used in the "names" variable in the equation definition
- 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
- 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
See also
Other Poisson Wrapper Functions:
EventAssignment.poisres()
,
LikelihoodBound.poisres()
,
PoisRun()
,
PoisRunJoint()
,
PoisRunMulti()
,
PoissonCurveSolver()
,
Residual.poisres()
,
RunPoissonEventAssignment()
,
RunPoissonEventAssignment_bound()
,
RunPoissonRegression_Joint_Omnibus()
,
RunPoissonRegression_Omnibus()
,
RunPoissonRegression_Residual()