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Estimate yearly age-specific mortality rates (ASMR) from a SOCSIM-generated population file

Source: R/estimate_rates.R
estimate_mortality_rates.Rd

Given a population file ('opop') generated by rsocsim, the function estimates (yearly) age-specific mortality rates.

Usage

estimate_mortality_rates(
  opop,
  final_sim_year,
  year_min,
  year_max,
  year_group,
  age_max_mort,
  age_group
)

Arguments

opop

An R object from SOCSIM microsimulation output (population file).

final_sim_year

numeric. Final simulated year in 'real world' time ( used to convert 'SOCSIM time' to 'real world' time.)

year_min

numeric. Lower-bound year for which rate should be estimated.

year_max

numeric. Upper-bound year for which rate should be estimated.

year_group

numeric. Size of year groups to estimate rate (year_group=1 will produce single-year estimates)

age_max_mort

numeric. Maximum age for estimating mortality.

age_group

numeric. Size of age groups to estimate rate (age_group=1 will produce single-age estimates)

Value

A data frame with columns year, sex, age, and socsim. year is a factor describing the grouped calendar-year interval, sex is "male" or "female", age is a factor describing the age interval, and socsim is the estimated mortality rate for that cell.

Details

The final_sim_year can be obtained from the .sup file and must refer to to a real-world year.

Grouped year and age ranges (i.e., if year_group > 1 or age_group > 1) are created as [year;year+year_group). For age_group > 1, mortality rates are split into an infant group [0,1) and then grouped ages [1, age_group), [age_group, age_group + age_group), and so on.

Examples

opop <- data.frame(
  pid = 1:6,
  fem = c(1, 0, 1, 0, 1, 1),
  group = 1,
  nev = 0,
  dob = c(120, 120, 336, 348, 180, 360),
  mom = c(0, 0, 1, 1, 0, 5),
  pop = c(0, 0, 2, 2, 0, 2),
  nesibm = 0,
  nesibp = 0,
  lborn = 0,
  marid = 0,
  mstat = 0,
  dod = c(0, 300, 0, 0, 0, 0),
  fmult = 0
)

asmr <- estimate_mortality_rates(opop = opop,
                     final_sim_year = 2021,
                     year_min = 1995,
                     year_max = 2000,
                     year_group = 5,
                     age_max_mort = 100,
                     age_group = 5)
head(asmr)
#> # A tibble: 6 × 4
#>   year        sex   age     socsim
#>   <fct>       <chr> <fct>    <dbl>
#> 1 [1995,2000) male  [0,1)       NA
#> 2 [1995,2000) male  [1,5)       NA
#> 3 [1995,2000) male  [5,10)      NA
#> 4 [1995,2000) male  [10,15)     NA
#> 5 [1995,2000) male  [15,20)     NA
#> 6 [1995,2000) male  [20,25)     NA