LongDecompHE (version 0.1.0)

Attribution_sullivan: Longitudinal Attribution of Disability and Death Based on Sullivan Method

Description

Computes the relative and/or absolute contributions of causes (i.e., covariates) to disability and death across a specified age range, based on a copula regression models with semiparametric additive hazards margins object. This attribution approach adopts a Sullivan method for cohort health expectancy.

Usage

Attribution_sullivan(object, type.attrib = "both")

Value

A list containing the following components:

Relative_Contributions_1

Matrix of relative contributions to disability prevalence by cause and age

Relative_Contributions_2

Matrix of relative contributions to death probability by cause and time

Absolute_Contributions_1

Matrix of absolute contributions to disability prevalence by cause and age

Absolute_Contributions_2

Matrix of absolute contributions to death probability by cause and time

var_list

Vector of covariate names used in the model

time_list

Vector of attribution ages

copula

Character indicating attribution type ("Attribution_sullivan")

#' Additional components copula and summary are included for compatibility with generic

Arguments

object

A fitted LongDecompHE object returned by copula_additive.

type.attrib

Type of attribution output to return; can be one of:

• "rel": Relative contributions of causes over age (i.e., time);

• "abs": Absolute contributions of causes over age (i.e., time);

• "both": Both relative and absolute contributions (default).

Details

This function loops over all attribution-eligible ages in the fitted model (from 0 to floor(u-1)), Use summary() on the returned object to print the attribution tables.

See Also

copula_additive for model fitting; summary.LongDecompHE for output methods.

Examples

# \donttest{
# Fit a model (see copula_additive)
data(simulated_dataA)
u1 = u2 = max(simulated_dataA$visit_time)
var_list = c("Z1", "Z2", "Z3")
copula_additive_model <-  copula_additive(data = simulated_dataA,
                                        var_list = var_list,
                                        l1=0, u1 = u1, m1 = 3,
                                        l2=0, u2 = u2, m2 = 3,
                                        method = "combined", iter=1000,
                                        stepsize=1e-6,
                                        hes = TRUE,
                                        control = list(maxit = 10000))
summary(copula_additive_model)
# Attribution analysis (both relative and absolute)
attributionA <- Attribution_sullivan(object = copula_additive_model, type.attrib = "both")
summary(attributionA)

# Relative only
attributionA_rel <- Attribution_sullivan(object = copula_additive_model, type.attrib = "rel")

# Absolute only
attributionA_abs <- Attribution_sullivan(object = copula_additive_model, type.attrib = "abs")
# }