ReadCHMD: Download the Canadian Human Mortality Database (CHMD)

In MortalityLaws: Parametric Mortality Models, Life Tables and HMD

Download the Canadian Human Mortality Database (CHMD)

Description

Download detailed mortality and population data for different provinces and territories in Canada, in a single object from the Canadian Human Mortality Database.

Usage

ReadCHMD(what, regions = NULL, interval = "1x1", save = FALSE, show = TRUE)

Arguments

what	What type of data are you looking for? The following options are available: "births" – birth records; "Dx_lexis" – deaths by Lexis triangles; "population" – population size; "Dx" – death counts; "Ex" – exposure-to-risk; "mx" – central death-rates; "LT_f" – period life tables for females; "LT_m" – period life tables for males; "LT_t" – period life tables both sexes combined; "e0" – period life expectancy at birth;
regions	Specify the region specific data you want to download by adding the CHMD region code/s. Options: "CAN" – Canada - Sum of Canadian provinces and territories; "NFL" – Newfoundland & Labrador; "PEI" – Prince Edward Island; "NSC" – Nova Scotia; "NBR" – New Brunswick; "QUE" – Quebec; "ONT" – Ontario; "MAN" – Manitoba; "SAS" – Saskatchewan; "ALB" – Alberta; "BCO" – British Columbia; "NWT" – Northwest Territories & Nunavut; "YUK" – Yukon; NULL – if NULL data for all the regions are downloaded.
interval	Datasets are given in various age and time formats based on which the records are agregated. Interval options: "1x1" – by age and year; "1x5" – by age and 5-year time interval; "1x10" – by age and 10-year time interval; "5x1" – by 5-year age group and year; "5x5" – by 5-year age group and 5-year time interval; "5x10" –by 5-year age group and 10-year time interval.
save	Do you want to save a copy of the dataset on your local machine? Logical. Default: FALSE.
show	Choose whether to display a progress bar. Logical. Default: TRUE.

Details

(Description taken from the CHMD website).

The Canadian Human Mortality Database (CHMD) was created to provide detailed Canadian mortality and population data to researchers, students, journalists, policy analysts, and others interested in the history of human longevity. The project is an achievement of the Mortality and Longevity research team at the Department of Demography, Universite de Montreal, under the supervision of Professor Robert Bourbeau, in collaboration with demographers at the Max Plank Institute for Demographic Research (Rostock, Germany) and the Department of Demography, University of California at Berkeley. Nadine Ouellette, researcher at the Institut national d'etudes demographiques in Paris and member of the Mortality and Longevity research team at the Universite de Montreal, is in charge of computing all CHMD life tables and updating the CHMD web site.

The CHMD is a "satellite" of the Human Mortality Database (HMD), an international database which currently holds detailed data for multiple countries or regions. Consequently, the CHMD's underlying methodology corresponds to the one used for the HMD.

The CHMD gathers all required data (deaths counts, births counts, population size, exposure-to-risk, death rates) to compute life tables for Canada, its provinces and its territories. One of the great advantages of the database is to include data that is validated and corrected, when required, and rendered comparable, if possible, for the period ranging from 1921 thru 2011. For comparison purposes, various life tables published by governmental organizations are also available for download in PDF format.

Value

A ReadCHMD object that contains:

input	List with the input values;
data	Data downloaded from CHMD;
download.date	Time stamp;
years	Numerical vector with the years covered in the data;
ages	Numerical vector with ages covered in the data.

Author(s)

Marius D. Pascariu

See Also

ReadHMD ReadAHMD

Examples

# Download demographic data for Quebec and Saskatchewan regions in 1x1 format

# Death counts. We don't want to export data outside R.
CHMD_Dx <- ReadCHMD(what = "Dx",
                    regions = c('QUE', 'SAS'),
                    interval  = "1x1",
                    save = FALSE)

# Download life tables for female population. To export data use save = TRUE.
LTF <- ReadCHMD(what = "LT_f",
                regions = c('QUE', 'SAS'),
                interval  = "1x1",
                save = FALSE)

MortalityLaws documentation built on Aug. 8, 2023, 5:10 p.m.