ggbseg {DDM}

estimate death registration coverage using the hybrid generalized growth balance and synthetic extinct generation

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.

Usage

ggbseg(X, minA = 15, maxA = 75, minAges = 8, exact.ages = NULL,
  eOpen = NULL, deaths.summed = FALSE)

Arguments

X

data.frame with columns, $pop1, $pop2, $deaths, $date1, $date2, $age, $sex, and $cod (if there are more than 1 region/sex/intercensal period).

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

optional. A user-specified vector of exact ages to use for coverage 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.

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 columns are given, then we assume January 1 dates. If year and month are given, then we assume dates on the first of the month. If you want coverage estimates for a variety of intercensal periods/regions/by sex, then stack them, and use a variable called $cod with a unique values for each data chunk. Different values of $cod could indicate sexes, regions, intercensal periods, etc. The $deaths column should refer to the average annual deaths in each age class in the intercensal period. Sometimes one uses the arithmetic average of recorded deaths in each age, or simply the average of the deaths around the time of census 1 and census 2. To identify an age-range in the traditional visual way, see plot.ggb(), when working with a single year/sex/region of data. The automatic age-range determination feature of this function tries to implement an intuitive way of picking ages that follows the advice typically given for doing so visually. We minimize the square of the average squared residual between the fitted line and right term. Finally, only specify eOpen when working with a single region/sex/period of data, otherwise the same value will be passed in irrespective of mortality and sex.

Value

a data.frame with columns for the coverage coefficient $coverage, and the minimum $lower and maximum $upper of the age range on which it is based. Rows indicate data partitions, as indicated by the optional $cod variable.

References

Hill K. Methods for measuring adult mortality in developing countries: a comparative review. The global burden of disease 2000 in aging populations. Research paper; No. 01.13; 2001.

Hill K, You D, Choi Y. Death distribution methods for estimating adult mortality: sensitivity analysis with simulated data errors. Demographic Research. 2009; 21:235-254.

Preston, S. H., Coale, A. J., Trussel, J. & Maxine, W. Estimating the completeness of reporting of adult deaths in populations that are approximately stable. Population Studies, 1980; v.4: 179-202

Examples

# The Mozambique data
res <- ggbseg(Moz)
res
# The Brasil data
BM <- ggbseg(BrasilMales)
BF <- ggbseg(BrasilFemales)
head(BM)
head(BF)