hiv {GJRM.data}R Documentation

HIV Zambian data

Description

HIV Zambian data by region, together with polygons describing the regions' shapes.

Usage

data(hiv)
data(hiv.polys)

Format

hiv is a 6416 row data frame with the following columns:

consent

binary variable indicating consent to test for HIV.

status

binary variable indicating whether an individual is HIV positive (status = 1) or not (status = 0).

age

age in years.

education

years of education.

wealth

wealth index.

region

code identifying region, and matching names(hiv.polys). It can take nine possible values: 1 central, 2 copperbelt, 3 eastern, 4 luapula, 5 lusaka, 6 northwestern, 7 northern, 8 southern, 9 western.

marital

never married, currently married, formerly married.

std

had a sexually transmitted disease.

highhiv

had high risk sex.

partner

number of partners.

condom

used condom during last intercourse.

aidscare

equal to 1 if would care for an HIV-infected relative.

knowsdiedofaids

equal to 1 if know someone who died of HIV.

evertestedHIV

equal to 1 if previously tested for HIV.

smoke

smoker or not.

ethnicity

bemba, lunda (luapula), lala, ushi, lamba, tonga, luvale, lunda (northwestern), mbunda, kaonde, lozi, chewa, nsenga, ngoni, mambwe, namwanga, tumbuka, other.

language

English, Bemba, Lozi, Nyanja, Tonga, other.

interviewerID

interviewer identifier.

agehadsex

age the individual had sex.

religion

four categories.

sw

survey weights.

hiv.polys contains the polygons defining the areas in the format described below.

Details

The data frame hiv relates to the regions whose boundaries are coded in hiv.polys. hiv.polys[[i]] is a 2 column matrix, containing the vertices of the polygons defining the boundary of the ith region. names(hiv.polys) matches hiv$region (order unimportant).

Source

The data have been produced as described in:

McGovern M.E., Barnighausen T., Marra G. and Radice R. (2015), On the Assumption of Joint Normality in Selection Models: A Copula Approach Applied to Estimating HIV Prevalence. Epidemiology, 26(2), 229-237.

References

Marra G., Radice R., Barnighausen T., Wood S.N. and McGovern M.E. (2017), A Simultaneous Equation Approach to Estimating HIV Prevalence with Non-Ignorable Missing Responses. Journal of the American Statistical Association, 112(518), 484-496.


[Package GJRM.data version 0.1-1 Index]