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Main model class

MultiStateModel.Rd

Main model class

Main model class

Public fields

system

A MultistateSystem

pk_model

A PKModel or NULL.

prior_only

Should the model ignore likelihood?

pk_only

Should the model ignore the entire hazard model part?

Methods

Public methods

Method get_normalizers()

Get normalization constants for each variable

Usage

MultistateModel$get_normalizers()

Returns

list

Method get_n_grid()

Get number of grid points used for integration.

Usage

MultistateModel$get_n_grid()

Returns

An integer

Method set_normalizers()

Set normalization constant for each variable (side effect)

Usage

MultistateModel$set_normalizers(data)

Arguments

data

A JointData object

Method get_auc_normalizers()

Get normalization constants for AUC (PK)

Usage

MultistateModel$get_auc_normalizers()

Returns

list

Method set_auc_normalizers()

Set normalization constants for AUC (side effect)

Usage

MultistateModel$set_auc_normalizers(loc = 0, scale = 1)

Arguments

loc

Location

scale

Scale

Method get_prior_mean_h0()

Get assumed prior mean baseline hazard rates.

Usage

MultistateModel$get_prior_mean_h0()

Returns

Numeric vector with length equal to number of transitions

Method set_prior_mean_h0()

Set assumed prior mean baseline hazard rates (side effect).

Usage

MultistateModel$set_prior_mean_h0(mean_h0)

Arguments

mean_h0

Numeric vector with length equal to number of transitions

Method set_prior_mean_h0_data()

Set assumed prior mean baseline hazard rates (side effect) based on average hazards in data.

Usage

MultistateModel$set_prior_mean_h0_data(data)

Arguments

data

A JointData or PathData object.

Method new()

Create model

Usage

MultistateModel$new(
  system,
  covariates = NULL,
  pk_model = NULL,
  t_max = 1000,
  num_knots = 5,
  categorical = NULL,
  n_grid = 1000,
  prior_only = FALSE,
  pk_only = FALSE
)

Arguments

system

A MultistateSystem

covariates

The names of the hazard covariates (excluding possible exposure estimated from PK model). Do not use reserved names ss_auc or dose.

pk_model

A PKModel or NULL.

t_max

Max time.

num_knots

Total number of spline knots.

categorical

Names of covariates that are binary. This only has an effect when simulating data. When fitting a model, all covariates are treated as continuous, so you should use a binary encoding for categories if there is more than two.

n_grid

Number of time discretization points for integrating

prior_only

Should the model ignore likelihood?

pk_only

Should the model ignore the entire hazard model part? hazards.

Method set_knots()

Set knot locations based on event times

The knots define how the spline basis functions are set.

Usage

MultistateModel$set_knots(t_max, t_event, num_knots)

Arguments

t_max

Max time

t_event

Occurred event times

num_knots

Total number of knots. Includes the boundary knots. Number of spline basis functions will be num_knots + 1.

Method get_knots()

Get knots

Usage

MultistateModel$get_knots()

Method get_tmax()

Get max time

Usage

MultistateModel$get_tmax()

Method get_states()

Get names of the states

Usage

MultistateModel$get_states()

Method has_pk()

Is there a PK submodel?

Usage

MultistateModel$has_pk()

Method print()

Print the object

Usage

MultistateModel$print()

Returns

nothing

Method covs()

Get the hazard covariates (including steady-state exposure if PK model is included)

Usage

MultistateModel$covs()

Method data_covs()

Get all covariates that need to be given as data

Usage

MultistateModel$data_covs(which = NULL)

Arguments

which

Which subset to get?

Method categ_covs()

Get names of categorical covariates

Usage

MultistateModel$categ_covs()

Method simulate_subjects()

Simulate subject data, all covariates independently.

Usage

MultistateModel$simulate_subjects(N_subject = 100, doses = c(15, 30, 60))

Arguments

N_subject

Number of subjects.

doses

Possible doses.

Method simulate_data()

Simulate data using the multistate model

Usage

MultistateModel$simulate_data(
  N_subject = 100,
  beta_haz = NULL,
  beta_pk = NULL,
  w0 = 0.001,
  w = NULL,
  num_doses = 10,
  subjects_df = NULL
)

Arguments

N_subject

Number of subjects.

beta_haz

Covariate effects on each transition type. A matrix of shape num_target_states x num_covs. If NULL, a data frame of zeros is used.

beta_pk

Covariate effects on PK parameters. A named list with three elements, each being a vector. If any element is NULL, a vector of zeros is used.

w0

Baseline hazard rate for all transitions.

w

Spline weights. Matrix of shape num_trans x num_weights. If NULL, a matrix of zeros is used.

num_doses

Average number of doses taken by each subject. Only has effect if model as a PK submodel.

subjects_df

Subject data frame. If NULL, simulated using the simulate_subjects method.

Returns

A JointData object.

Method target_states()

Get indices of states that are not source states

Usage

MultistateModel$target_states()

Returns

integer

Method clone()

The objects of this class are cloneable with this method.

Usage

MultistateModel$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.