# LifeTable: Compute Life Tables from Mortality Data In MortalityLaws: Parametric Mortality Models, Life Tables and HMD

 LifeTable R Documentation

## Compute Life Tables from Mortality Data

### Description

Construct either a full or abridged life table with various input choices like: death counts and mid-interval population estimates `(Dx, Ex)` or age-specific death rates `(mx)` or death probabilities `(qx)` or survivorship curve `(lx)` or a distribution of deaths `(dx)`. If one of these options is specified, the other can be ignored. The input data can be an object of class: numerical `vector`, `matrix` or `data.frame`.

### Usage

``````LifeTable(x, Dx = NULL, Ex = NULL,
mx = NULL,
qx = NULL,
lx = NULL,
dx = NULL,
sex = NULL,
lx0 = 1e5,
ax  = NULL)
``````

### Arguments

 `x` Vector of ages at the beginning of the age interval. `Dx` Object containing death counts. An element of the `Dx` object represents the number of deaths during the year to persons aged x to x+n. `Ex` Exposure in the period. `Ex` can be approximated by the mid-year population aged x to x+n. `mx` Life table death rate in age interval [x, x+n). `qx` Probability of dying in age interval [x, x+n). `lx` Probability of survival up until exact age x (if l(0) = 1), or the number of survivors at exact age x, assuming l(0) > 1. `dx` Deaths by life-table population in the age interval [x, x+n). `sex` Sex of the population considered here. Default: `NULL`. This argument affects the first two values in the life table ax column. If sex is specified the values are computed based on the Coale-Demeny method and are slightly different for males than for females. Options: `NULL, male, female, total`. `lx0` Radix. Default: 100 000. `ax` Numeric scalar. Subject-time alive in age-interval for those who die in the same interval. If `NULL` this will be estimated. A common assumption is `ax = 0.5`, i.e. the deaths occur in the middle of the interval. Default: `NULL`.

### Details

The "life table" is also called "mortality table" or "actuarial table". This shows, for each age, what the probability is that a person of that age will die before his or her next birthday, the expectation of life across different age ranges or the survivorship of people from a certain population.

### Value

The output is of the `"LifeTable"` class with the components:

 `lt` Computed life table; `call` `Call` in which all of the specified arguments are specified by their full names; `process_date` Time stamp.

### Author(s)

Marius D. Pascariu

`LawTable` `convertFx`

### Examples

``````# Example 1 --- Full life tables with different inputs ---

y  <- 1900
x  <- as.numeric(rownames(ahmd\$mx))
Dx <- ahmd\$Dx[, paste(y)]
Ex <- ahmd\$Ex[, paste(y)]

LT1 <- LifeTable(x, Dx = Dx, Ex = Ex)
LT2 <- LifeTable(x, mx = LT1\$lt\$mx)
LT3 <- LifeTable(x, qx = LT1\$lt\$qx)
LT4 <- LifeTable(x, lx = LT1\$lt\$lx)
LT5 <- LifeTable(x, dx = LT1\$lt\$dx)

LT1
LT5
ls(LT5)

# Example 2 --- Compute multiple life tables at once ---

LTs = LifeTable(x, mx = ahmd\$mx)
LTs
# A warning is printed if the input contains missing values.
# Some of the missing values can be handled by the function.

# Example 3 --- Abridged life table ------------

x  <- c(0, 1, seq(5, 110, by = 5))
mx <- c(.053, .005, .001, .0012, .0018, .002, .003, .004,
.004, .005, .006, .0093, .0129, .019, .031, .049,
.084, .129, .180, .2354, .3085, .390, .478, .551)
LT6 <- LifeTable(x, mx = mx, sex = "female")
LT6

# Example 4 --- Abridged life table w using my own 'ax' ------------
# In this examples we are using the ages (x) and death rates (mx) from
# example 3. Note that 'ax' must have the same length as the 'x' vector
# otherwise an error message will be returned.

my_ax <- c(0.1, 1.5, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1)

LT7 <- LifeTable(x = x, mx = mx, ax = my_ax)

``````

MortalityLaws documentation built on Aug. 8, 2023, 5:10 p.m.