pempi
OverviewThe proportion estimation with marginal proxy information
(pempi
) package, allows to estimate and build confidence
intervals for proportions, from random or stratified samples and census
data with participation bias. Measurement errors in the form of false
positive and false negative are also included in the inferential
procedure. The pempi
package also contains code for
simulation studies and sensitivity analysis reported in the companion
paper Guerrier et al. (2023), as well as the Austrian dataset on
COVID-19 prevalence in November 2020.
The notation and conventions used in Guerrier et al. (2023) are slightly amended for convenience in this package. In particular, we use R1 instead R11, R2 instead of R10, R3 instead of R01 and R4 instead of R00.
The pempi
package can be installed from GitHub as
follows:
# Install devtools
install.packages("devtools")
# Install the package from GitHub
::install_github("stephaneguerrier/pempi") devtools
Note that Windows users are assumed that have Rtools installed (if this is not the case, please visit this link).
@Manual{guerrier2023cape,
title = {{pempi}: Proportion estimation with marginal proxy information},
author = {Guerrier, S and Kuzmics, C and Victoria-Feser, M.-P.},
year = {2023},
note = {R package},
url = {https://github.com/stephaneguerrier/pempi}
}
The license this source code is released under is the GNU AFFERO GENERAL PUBLIC LICENSE (AGPL) v3.0. Please see the LICENSE file for full text. Otherwise, please consult GNU which will provide a synopsis of the restrictions placed upon the code.
Guerrier, Stéphane, Christoph Kuzmics, and Maria-Pia Victoria-Feser. 2023. “Assessing COVID-19 Prevalence in Austria with Infection Surveys and Case Count Data as Auxiliary Information”, https://arxiv.org/abs/2012.10745.