lyl_aggregated_range {lillies}

Life Years Lost at a range of different ages using aggregated data.

Description

lyl estimates differences in remaining life expectancy and Life Years Lost for two given life tables data and data0 after a range of specific ages (age_begin to age_end) and restrictied to a maximum theoretical age \tau.

Usage

lyl_aggregated_range(
  data,
  age,
  rates,
  surv,
  weights,
  data0,
  age0,
  rates0,
  surv0,
  age_begin,
  age_end,
  censoring_label = "Alive",
  death_labels = "Dead",
  tau = 100
)

Arguments

data

A dataframe, where each raw represents an age, for the population of interest. The dataframe will contain information on age-specific mortality rates or survivial probability (if both parameters are provided, rates will be used).

age

Variable in data containing information on age.

rates

Variable in data containing information on age-specific mortality rates.

surv

Variable in data containing information on age-specific survival probability.

weights

Variable in data containing information on number of new cases per age. A weighted average is provided using these weights.

data0

A dataframe, where each raw represents an age, for the population of reference The dataframe will contain information on age-specific mortality rates or survivial probability (if both parameters are provided, rates will be used).

age0

Variable in data0 containing information on age.

rates0

Variable in data0 containing information on age-specific mortality rates.

surv0

Variable in data0 containing information on age-specific survival probability.

age_begin

Specific starting age at which the Life Years Lost have to be estimated.

age_end

Specific ending age at which the Life Years Lost have to be estimated.

censoring_label

Label for censoring status ("Alive" by default).

death_labels

Label for event status ("Dead" by default).

tau

Remaining life expectancy and Life Years Lost are estimated restrictied to a maximum theoretical age \tau (\tau=100 years by default).

Value

A list with class "lyl_aggregated" containing the following components:

• data: Name of the dataset preovided in parameter data

• data0: Name of the dataset preovided in parameter data0

• LYL: Data frame with 1 observation and 2 variables: life_exp and life_exp0 which are the estimated remaining life expectancies averaged over the age range and before age tau years for the population provided in data and data0, respectively

• tau: Maximum theoretical age \tau

• age_begin: Specific starting age at which the Life Years Lost have been estimated

• age_end: Specific ending age at which the Life Years Lost have been estimated

• data_plot: A data frame in long format with 3 variables time, cause, and cip used to create a Figure of Life Years Lost with function plot.

• censoring_label: Label for censoring status

• death_labels: Label(s) for death status

• type: Whether the estimation is at "age_specific" or "age_range".

References

• Andersen PK. Life years lost among patients with a given disease. Statistics in Medicine. 2017;36(22):3573- 3582.

• Andersen PK. Decomposition of number of life years lost according to causes of death. Statistics in Medicine. 2013;32(30):5278-5285.

• Plana-Ripoll et al. lillies – An R package for the estimation of excess Life Years Lost among patients with a given disease or condition. PLoS ONE. 2020;15(3):e0228073.#'

See Also

• lyl_aggregated for estimation of Life Years Lost at one specific age.

• summary.lyl_aggregated to summarize objects obtained with function lyl_aggregated_range.

Examples

# Load simulated data as example
data(aggreg_data)
data(pop_ref)

# Estimate remaining life expectancy and Life Years
# Lost after each age from 40 to 89 years and before age 90 years
lyl_summary_data <- lyl_aggregated_range(data = aggreg_data, age = age,
                                         rates = rate, weights = new_cases,
                                         data0 = pop_ref, age0 = age, surv0 = survival,
                                         age_begin = 40, age_end = 89, tau = 90)

# Summarize the data
summary(lyl_summary_data)