Description
Creating Actuarial Life Tables.
Description
Contains data and functions that can be used to make actuarial life tables. Each function adds a column to the inputted dataset for each intermediate calculation between mortality rate and life expectancy. Users can run any of our functions to complete the life table until that step, or run lifetable() to output a full life table that can be customized to remove optional columns. Methods for creating lifetables are as described in Zedstatistics (2021) <https://www.youtube.com/watch?v=Dfe59glNXAQ>.
README.md
actLifer
The actLifer package contains functions that create a life table based on mortality data, and ultimately calculates life expectancy from data on annual deaths for given ages/age groups. This package also contains mortality data from CDC wonder.
This package will be useful for actuaries, epidemiologists, or any data scientists working with mortality data.
Installation
You can install the development version of actLifer from GitHub with:
# install.packages("devtools")
devtools::install_github("g-rade/actLifer")
You can install the reslease version of actLifer from CRAN with:
#install.packages("actLifer")
How to use actLifer
library(actLifer)
#> Loading required package: dplyr
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
## Take a look at the mortality2 data fram
head(mortality2)
#> # A tibble: 6 × 3
#> age_group deaths population
#> <chr> <dbl> <dbl>
#> 1 < 1 year 23161 3970145
#> 2 1 year 1568 3995008
#> 3 2 years 1046 3992154
#> 4 3 years 791 3982074
#> 5 4 years 640 3987656
#> 6 5 years 546 4032515
## Use the lifetable function to make a custom life table with just
## CentralDeathRate, PropToSurvive, and LifeExpectancy by setting includeAllSteps = FALSE
lifetable(mortality2, "age_group", "population", "deaths", FALSE, TRUE, TRUE)
#> # A tibble: 85 × 6
#> age_group deaths population CentralDeathRate PropToSurvive LifeExpectancy
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 < 1 year 23161 3970145 0.00583 1 75.9
#> 2 1 year 1568 3995008 0.000392 0.994 75.3
#> 3 2 years 1046 3992154 0.000262 0.994 74.4
#> 4 3 years 791 3982074 0.000199 0.994 73.4
#> 5 4 years 640 3987656 0.000160 0.993 72.4
#> 6 5 years 546 4032515 0.000135 0.993 71.4
#> 7 6 years 488 4029655 0.000121 0.993 70.4
#> 8 7 years 511 4029991 0.000127 0.993 69.4
#> 9 8 years 483 4159114 0.000116 0.993 68.4
#> 10 9 years 462 4178524 0.000111 0.993 67.4
#> # ℹ 75 more rows
## Or show everything by setting includeAllSteps=TRUE, includeCDR=TRUE, and includePS=TRUE which are the default values
lifetable(mortality2, "age_group", "population", "deaths")
#> # A tibble: 85 × 11
#> age_group deaths population CentralDeathRate ConditionalProbDeath
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 < 1 year 23161 3970145 0.00583 0.00582
#> 2 1 year 1568 3995008 0.000392 0.000392
#> 3 2 years 1046 3992154 0.000262 0.000262
#> 4 3 years 791 3982074 0.000199 0.000199
#> 5 4 years 640 3987656 0.000160 0.000160
#> 6 5 years 546 4032515 0.000135 0.000135
#> 7 6 years 488 4029655 0.000121 0.000121
#> 8 7 years 511 4029991 0.000127 0.000127
#> 9 8 years 483 4159114 0.000116 0.000116
#> 10 9 years 462 4178524 0.000111 0.000111
#> # ℹ 75 more rows
#> # ℹ 6 more variables: ConditionalProbLife <dbl>, NumberToSurvive <dbl>,
#> # PropToSurvive <dbl>, PersonYears <dbl>, TotalYears <dbl>,
#> # LifeExpectancy <dbl>