ReGenesees (R evolved Generalised software for sampling estimates and errors in surveys)

  • Ascolta questa pagina usando ReadSpeaker
  • Condividi
  • Lascia un feedback

The contents related to ReGenesees are shown in the following sections:

Description

ReGenesees (R Evolved Generalized Software for Sampling Estimates and Errors in Surveys) is a full-fledged R software for design-based and model-assisted analysis of complex sample surveys.

This system is the outcome of a long-term research and development project, aimed at defining a new Istat standard for calibration, estimation and sampling error assessment in large-scale sample surveys.

Main Statistical Functions

  • Complex Sampling Designs
    • Multistage, stratified, clustered, sampling designs
    • Sampling with equal or unequal probabilities, with or without replacement
    • “Mixed” sampling designs (i.e. with both self‑representing and non‑self‑representing strata)
  • Calibration
    • Global and partitioned (for factorizable calibration models)
    • Unit‑level and cluster‑level weights adjustment
    • Homoscedastic and heteroscedastic models
    • Linear, raking and logit distance functions
    • Bounded and unbounded weights adjustment
    • Multi‑step calibration
    • Calibration on multiple regression coefficients
    • Consistent trimming of calibration weights
  • Basic Estimators
    • Horvitz-Thompson
    • Calibration Estimators
  • Variance Estimation
    • Multistage formulation
    • Ultimate Cluster approximation
    • Collapsed strata technique for handling lonely PSUs
    • Taylor‑linearization of nonlinear “smooth” estimators
    • Generalized Variance Functions method
  • Estimates and Sampling Errors (standard error, variance, coefficient of variation, confidence interval, design effect) for:
    • Totals
    • Means
    • Absolute and relative frequency distributions (marginal, conditional and joint)
    • Ratios between totals
    • Shares and ratios between shares
    • Multiple regression coefficients
    • Quantiles
    • Population variance and standard deviation of numeric variables
    • Measures of Change derived from two not necessarily independent samples
  • Estimates and Sampling Errors for Complex Estimators
    • Handles arbitrary differentiable functions of Horvitz‑Thompson or Calibration estimators
    • Complex Estimators can be freely defined by the user
    • Automated Taylor‑linearization
    • Design covariance and correlation between Complex Estimators
  • Estimates and Sampling Errors for Subpopulations (Domains)
  • Sample Size Requirements and Power Calculations for:
    • Estimators of proportions and comparisons between two proportions
    • Estimators of means and comparisons between two means

System Architecture

The ReGenesees system has a clear-cut two-layer architecture. The application layer of the system is embedded into an R package named ReGenesees. A second R package, called ReGenesees.GUI, implements the presentation layer of the system (namely a Tcl/Tk GUI). Both packages can be run under Windows as well as under Mac, Linux and most of the Unix-like operating systems.

While the ReGenesees.GUI package requires the ReGenesees package, the latter can be used also without the GUI on its top. This means that the statistical functions of the system will always be accessible by users interacting with R through the traditional command-line. On the contrary, less experienced R users will take advantage from the user-friendly mouse-click graphical interface.

Information

Status: validated
Author: Istat
Licence: EUPL-1.1
GSBPM code: 5.6 Calculate weights
5.7 Calculate aggregates
Programming language: R
Language of the GUI: EN
Keywords: calibration, estimation, variance estimation, complex surveys, complex estimators, automated linearization, R
Contact: name: Diego Zardetto
email: zardetto@istat.it

Software and documentation

SOFTWARE DEPENDENCIES for package ReGenesees

R ( ≥ 2.14.0)

SOFTWARE DEPENDENCIES for package ReGenesees.GUI

R ( ≥ 2.14.0)

R packages: ReGenesees, tcltk2, RODBC and svMisc

COPYRIGHT

Copyright 2015 Istat

Licensed under the European Union Public Licence (EUPL), version 1.1 or subsequent. You may not use this work except in compliance with the Licence. You may obtain a copy of the Licence at: http://ec.europa.eu/idabc/eupl.html. 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.

DISCLAIMER

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.

DOWNLOAD
Release date: 13/12/2023

Package ReGenesees (statistical engine)

Package ReGenesees.GUI (graphical user interface)

INSTALLATION

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

Reference manual -ReGenesees v. 2.3

Reference manual – ReGeneseesGUI v. 2.3

OTHER DOCUMENTATION

ReGenesees website

Fallows, A., M. Pope, J. Digby-North, G. Brown, and D. Lewis. 2015. “A Comparative Study of Complex Survey Estimation Software in ONS“. Romanian Statistical Review, 3:46-64.

Zardetto, D. 2015. “ReGenesees: an Advanced R System for Calibration, Estimation and Sampling Error Assessment in Complex Sample Surveys“. Journal of Official Statistics, Volume 31, N. 2: 177-203.

Zardetto, D. 2013. “ReGenesees: an Advanced R System for Calibration, Estimation and Sampling Errors Assessment in Complex Sample Surveys“. In Proceedings of the 7th International Conferences on New Techniques and Technologies for Statistics (NTTS). Eurostat, Brussels, 5-7 March 2013.

Barcaroli, G., and D. Zardetto. 2012. “Use of R in Business Surveys at the Italian National Institute of Statistics: Experiences and Perspectives“. In Proceedings of the 4th International Conference of Establishment Surveys (ICES IV). American Statistical Association, Montréal, 11-14 June 2012.

Last edit: 13 December 2023