The ahri
R library provides functions for estimating the HIV incidence
rate with Africa Health Research Institute
(AHRI) data. These
functions can read in the AHRI datasets, write them to .Rda format,
standardize and subset the data, impute the HIV infection events, and
calculate unadjused or age-adjusted HIV incidence rates using a single
or multiple imputation approach.
The wiki help pages serve as a short introduction to the ahri
library.
These can be found in the links below. The help files are organised as
follows:
Getting started, which describes how to install the ahri
library,
which AHRI datasets to request and where to put them. It also shows
how to set the paths to these datasets.
https://github.com/vando026/ahri/wiki/1-Getting-started
Reading and writing the datasets, which describes the functions for performing these operations. https://github.com/vando026/ahri/wiki/2-Read-functions
Set functions, which describes a range of functions for processing the data, subsetting the data, and other data transformations. https://github.com/vando026/ahri/wiki/3-Set-functions
Utility functions commonly used with HIV incidnece analyses. https://github.com/vando026/ahri/wiki/4-Utility-functions
Functions to make the HIV incidence datasets, impute the HIV dates, perform mid-point, end-point, or single random-point imputation, and calculate the HIV incidence rates by sex or year using multiple imputation. https://github.com/vando026/ahri/wiki/5A-HIV-functions and https://github.com/vando026/ahri/wiki/5B-HIV-functions
G-imputation functions to impute the HIV times conditional on auxiliary data. https://github.com/vando026/ahri/wiki/6-G-Imputation
There are other sources of help:
The ahri
package has help files and documentation. Type ?ahri
to
get to the help pages. For more information on a specific function,
for example setFiles
, type ?setFiles
.
Please consult the issues page on this Github site for more information and for answers to questions someone before you may have already asked.
There is a Python
version of this
library that speads up the
HIV incidence calculations.
Read and load the data, subset and create repeat-tester data.
Calculate the HIV incidence rate for women aged 15–24 years. Do 3 imputed datasets using the single-random point method.
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