lyl_range {lillies} | R Documentation |
Life Years Lost at a range of different ages.
Description
lyl
estimates remaining life expectancy and Life Years Lost for a given population
after a range of specific ages (age_begin
to age_end
) and restrictied to
a maximum theoretical age \tau
.
Usage
lyl_range(
data,
t0 = NULL,
t,
status,
age_begin,
age_end,
censoring_label = "Alive",
death_labels = "Dead",
tau = 100
)
Arguments
data |
A dataframe, where each raw represents a person. The dataframe will
have a time-to-event format with at least two variables: age at end of follow-up ( |
t0 |
Age at start of the follow-up time. Default is |
t |
Age at the end of the follow-up time (death or censoring). |
status |
Status indicator, normally 0=alive, 1=dead. Other choices are
TRUE/FALSE (TRUE = death) or 1/2 (2=death). For multiple causes of death (competing risks
analysis), the status variable will be a factor, whose first level is treated as censoring; or
a numeric variable, whose lowest level is treated as censoring. In the latter case,
the label for censoring is |
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. If |
death_labels |
Label for event status. For only one cause of death, |
tau |
Remaining life expectancy and Life Years Lost are estimated restrictied to a maximum
theoretical age |
Value
A list with class "lyl_range"
containing the following components:
data
: Data frame with 3 variables and as many observations as the original data provided to estimate Life Years Lost:t0
,t
, andstatus
LYL
: Data frame with(age_end - age_begin + 1)
observations and at least 3 variables:age
which corresponds to each specific age fromage_begin
toage_end
;life_exp
which is the estimated remaining life expectancy at age specific age and before agetau
years; and one variable corresponding to the estimated Life Years Lost for each specific cause of death. If only one cause of death is considered (no competing risks), this variable isDead
and includes the total overall Life Years Losttau
: Maximum theoretical age\tau
age_begin
: Specific starting age at which the Life Years Lost have been estimatedage_end
: Specific ending age at which the Life Years Lost have been estimatedcensoring_label
: Label for censoring statusdeath_labels
: Label(s) for death statuscompeting_risks
: Logical value (TRUE
= more than one cause of death (competing risks))numbers_at_risk
: Data frame with(tau - age_begin + 1)
observations and 2 variables:age
which corresponds to each specific age fromage_begin
totau
; andnumber
which is the number of persons at risk of dying at each specific agetype
: 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
for estimation of Life Years Lost at one specific age.lyl_diff
to compare average Life Years Lost for two populations.lyl_checkplot
to check whether small numbers could compromise the estimation.lyl_ci
to estimate bootstrapped confidence intervals.summary.lyl_range
to summarize objects obtained with functionlyl_range
.plot.lyl_range
to plot objects obtained with functionlyl_range
.
Examples
# Load simulated data as example
data(simu_data)
# Estimate remaining life expectancy and Life Years
# Lost after each age from 0 to 94 years and before age 95 years
lyl_estimation <- lyl_range(data = simu_data, t = age_death, status = death,
age_begin = 0, age_end = 94, tau = 95)
# Visualize data at each different specific age
summary(lyl_estimation)
plot(lyl_estimation)
# Summarize data over an age distribution
summary(lyl_estimation, weights = simu_data$age_disease)
# Estimate remaining life expectancy and Life Years
# Lost due to specific causes of death after each age
# from 0 to 94 years and before age 95 years
lyl_estimation2 <- lyl_range(data = simu_data, t = age_death, status = cause_death,
age_begin = 0, age_end = 94, tau = 95)
# Visualize data at each different specific age
summary(lyl_estimation2)
plot(lyl_estimation2)
# Summarize data over an age distribution
summary(lyl_estimation2, weights = simu_data$age_disease)