Age and cause decomposition of differences in life expectancies

Age and cause decomposition of differences in life expectancies

Usage

mdecomp(mx1, mx2, age, method = "andreev", ...)

Arguments

mx1

List of numeric arrays. 1st array should be all-cause nmx in the 1st population, other arrays are cause-specific nmx in the 1st population

mx2

List of numeric arrays. 1st array should be all-cause nmx in the 2nd population, other arrays are cause-specific nmx in the 2nd population

age

Numeric array of age intervals; for full life table = 0:100; for concise life table = c(0:1, seq(5,85,5))

method

Character. Decomposition method. "andreev" (1982) or "arriaga" (1984) - slightly different in their results. By default, method = "andreev".

...

Optional. Additional arguments for decomp().

Value

Dataframe with 1st column as overall decomposition (ex12), and other columns are decomposition by causes (cause(i))

Details

The contribution of each cause \(c\) to the absolute difference in life expectancies between the first and second population is caculated as $$\Delta_{x,c} = \frac{m^1_{x,c} - m^2_{x,c}}{m^1_{x} - m^2_{x}} \times \Delta_{x}$$ where \(\Delta_{x}\) is contribution of age \(x\) to difference \(e_0^2 - e_0^1\) from function decomp(), \(m^i_{x,c}\) is age-specific mortality rate for population \(i\) from cause \(c\), and \(m^i_x\) is total age-specific mortality rate.

See also

decomp() for just age decomposition and plot.mdecomp() for graph of mdecomp results