This function creates a life table based on the life table from Public Health England that lives here. It is designed to work with grouped data so that you can calculate life tables for multiple groups at once.
Usage
make_life_table(data,
grouping_vars = NULL,
age_cat_var = "age_cat",
deaths_var = "deaths",
population_var = "population")Arguments
- data
a 2x2 data frame with variables for age categories, population years and death count.
- grouping_vars
a list of variables used to group the output.
- age_cat_var
the name of the variable with age categories if the variable has a name other than "age_cat". Age categories should be in the format
start_age-end_age, ex:0-4,5-9, etc- deaths_var
the name of the variable with death counts if the variable has a name other than "deaths"
- population_var
the name of the variable with the population years if the variable has a name other than "population"
Examples
# step 1: generate data from which to calculate life expectancy
test_data <- data.frame(
group = c(rep("phe", 20), rep("simulated", 20)),
ages = rep(c("0", "1-4", "5-9", "10-14", "15-19","20-24", "25-29", "30-34", "35-39", "40-44",
"45-49", "50-54", "55-59", "60-64", "65-69", "70-74", "75-79", "80-84", "85-89", "90+"), 2),
deaths = c(206, 37, 23, 23, 105, 162, 268, 314, 413, 584, 954,
1359, 1912, 2824, 4507, 5851, 7117, 8192, 7745, 6442,
232, 30, 41, 22, 194, 168, 315, 313, 406, 643, 963,
1446, 1979, 2814, 4587, 5874, 7111, 8221, 7825, 6540),
population_est = c(50698, 215400, 280458, 258105, 282062, 329060, 306097, 274544, 260415,
267450, 311314, 324311, 296825, 271339, 284608, 228062, 162785, 111263, 58987, 26016,
51578, 215512, 279462, 257256, 282348, 329111, 306514, 274397, 259847, 267045,
311791, 323739, 297453, 271344, 285047, 227655, 162922, 110554, 58886, 26243))
# step 2: create a life table using the methods from Public Health England .xlsm file
le_table <- make_life_table(data = test_data,
grouping_vars = c("group"),
age_cat_var = "ages",
population_var = "population_est")
# step 3: pull out the life expectancy for each group
## 3a: get le for age 0 (typical estimation used) with confidence intervals
get_le(le_table, grouping_vars = c("group"))
#> group obs_le_int ci_low_95 ci_high_95
#> 1 phe 78.32451 78.2 78.4
#> 21 simulated 77.99384 77.9 78.1
## 3b. get le for the age group starting at 30 without confidence intervals
get_le(le_table, start_age = 30, grouping_vars = c("group"), include_ci = FALSE)
#> group obs_le_int
#> 8 phe 49.23220
#> 28 simulated 49.08431