ggbsegCoverageFromYear: estimate death registration coverage for a single...

In albinomatheus/toolbox: Matheus' personal functions and palettes

estimate death registration coverage for a single year/sex/region using the modified Bennett-Horiuchi method

Description

Given two censuses and an average annual number of deaths in each age class between censuses, we can use stable population assumptions to estimate the degree of underregistration of deaths. The method estimates age-specific degrees of coverage. The age pattern of these is assumed to be noisy, so we take the arithmetic mean over some range of ages. One may either specify a particular age-range, or let the age range be determined automatically. If the age-range is found automatically, this is done using the method developed for the generalized growth-balance method. Part of this method relies on a prior value for remaining life expectancy in the open age group. By default, this is estimated using a standard reference to the Coale-Demeny West model life table, although the user may also supply a value. The difference between this method and seg() is that here we adjust census 1 part way through processing, based on some calculations similar to GGB. Called by ggbseg(). Users probably do not need to use this function directly.

Usage

ggbsegCoverageFromYear(
  codi,
  minA = 15,
  maxA = 75,
  minAges = 8,
  exact.ages.ggb = NULL,
  exact.ages.seg = NULL,
  eOpen = NULL,
  deaths.summed = FALSE,
  mig.summed = deaths.summed,
  lm.method = "oldschool",
  nx.method = 2,
  opt.method = "r2"
)

Arguments

codi	a chunk of data (single sex, year, region, etc) with all columns created by ggbsegMakeColumns()
minA	the lowest age to be included in search
maxA	the highest age to be included in search (the lower bound thereof)
minAges	the minimum number of adjacent ages to be used in estimating
exact.ages.ggb	optional. A user-specified vector of exact ages to use for coverage estimation in the GGB (first stage) part of the estimation.
exact.ages.seg	optional. A user-specified vector of exact ages to use for coverage estimation in the SEG (second stage) part of the estimation.
eOpen	optional. A user-specified value for remaining life-expectancy in the open age group.
deaths.summed	logical. Is the deaths column given as the total per age in the intercensal period (TRUE). By default we assume FALSE, i.e. that the average annual was given.
mig.summed	logical. Is the (optional) net migration column mig given as the total per age in the intercensal period (TRUE). By default we assume FALSE, i.e. that the average annual was given.
lm.method	character, one of: "oldschool" default sd ratio operation of still unknown origin "lm" or "ols" for a simple linear model "tls", "orthogonal", or "deming" for total least squares "tukey", "resistant", or ""median" for Tukey's resistant line method
nx.method	integer. either 2 or 4. 4 is smoother.
opt.method	What should we try to minimize when picking ggb age trims? Current options are "RMSE", "ORSS", "MAE", "MAPE", or "r2". Default "r2".

Details

Census dates can be given in a variety of ways: 1) using Date classes, and column names $date1 and $date2 (or an unambiguous character string of the date, like, "1981-05-13") or 2) by giving column names "day1","month1","year1","day2","month2","year2" containing integers. If only year1 and year2 are given, then we assume January 1 dates. If year and month are given, then we assume dates on the first of the month.

Value

a data.frame with columns for the coverage coefficient, and the min and max of the age range on which it is based.

albinomatheus/toolbox documentation built on June 13, 2024, 5:42 a.m.