The contents related to R2BEAT are shown in the following sections:
Multivariate optimal allocation for different domains in one and two stages stratified sample design. R2BEAT extends the Neyman (1934) – Tschuprow (1923) allocation method to the case of several variables, adopting a generalization of the Bethel’s proposal (1989). R2BEAT develops this methodology but, moreover, it allows to determine the sample allocation in the multivariate and multi-domains case of estimates for two-stage stratified samples. It also allows to perform Primary Stage Units selection.
R2BEAT easily manages all the complexity due to the optimal sample allocation in two-stage sampling design and provides several outputs for evaluating the allocation. Its name stands for “R ‘to’ Bethel Extended Allocation for Two-stage”. It is an extension of another open-source software called Mauss-R (Multivariate Allocation of Units in Sampling Surveys), implemented by ISTAT researchers. Mauss-R determines the optimal sample allocation in multivariate and multi-domains estimation, for one-stage stratified samples.
|GSBPM Codification:||2.4 Design frame and sample
4.1 Create frame and select sample
|Keywords:||sampling, two-stages, optimal allocation, multivariate, multi domain, stratified|
|Maintainer Contact:|| Andrea Fasulo
Copyright 2021 Istat
Licensed under the European Union Public Licence (EUPL), version 1.2 or subsequent. You may not use this work except in compliance with the Licence. You may obtain a copy of the Licence at: https://joinup.ec.europa.eu/collection/eupl/eupl-text-eupl-12. Unless required by applicable law or agreed to in writing, software distributed under the Licence is distributed on an “AS IS” basis, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the Licence for the specific language governing permissions and limitations under the Licence.
Istat assumes no responsibility for the results arising from use of the instrument that is inconsistent with the methodological guidance contained in the documentation available.
Install the downloaded package from within R as follows:
> install.packages(path_to_file, repos = NULL)
where the character path_to_file is the path to the .zip or .tar.gz file you downloaded.
TECHNICAL AND METHODOLOGICAL DOCUMENTATION