The lifetables 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.
You can install the development version of lifetables from GitHub with:
# install.packages("devtools")
devtools::install_github("g-rade/lifetables", build_vignettes=TRUE)library(lifetables)
#> 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
#> # … with 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 Central…¹ Condi…² Condi…³ Numbe…⁴ PropT…⁵ Perso…⁶
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 < 1 year 23161 3970145 0.00583 5.82e-3 0.994 100000 1 99709.
#> 2 1 year 1568 3995008 0.000392 3.92e-4 1.00 99418. 0.994 99399.
#> 3 2 years 1046 3992154 0.000262 2.62e-4 1.00 99379. 0.994 99366.
#> 4 3 years 791 3982074 0.000199 1.99e-4 1.00 99353. 0.994 99343.
#> 5 4 years 640 3987656 0.000160 1.60e-4 1.00 99334. 0.993 99326.
#> 6 5 years 546 4032515 0.000135 1.35e-4 1.00 99318. 0.993 99311.
#> 7 6 years 488 4029655 0.000121 1.21e-4 1.00 99304. 0.993 99298.
#> 8 7 years 511 4029991 0.000127 1.27e-4 1.00 99292. 0.993 99286.
#> 9 8 years 483 4159114 0.000116 1.16e-4 1.00 99280. 0.993 99274.
#> 10 9 years 462 4178524 0.000111 1.11e-4 1.00 99268. 0.993 99263.
#> # … with 75 more rows, 2 more variables: TotalYears <dbl>,
#> # LifeExpectancy <dbl>, and abbreviated variable names ¹CentralDeathRate,
#> # ²ConditionalProbDeath, ³ConditionalProbLife, ⁴NumberToSurvive,
#> # ⁵PropToSurvive, ⁶PersonYears