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ReGenesees System

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Description

ReGenesees (R evolved Generalised software for sampling estimates and errors in surveys) is an R-based, full-fledged software system for design-based and model-assisted analysis of complex sample surveys. ReGenesees has a clear-cut two-layer architecture: the application layer of the system is embedded into an R package named itself ReGenesees. A second R package, called ReGenesees.GUI, implements the presentation layer of the system. Both packages can be run under Windows, Mac, as well as under 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. Thus the statistical functions of the system will always be accessible by users interacting with R through the traditional command-line interface. On the contrary, less experienced R users will take advantage from the user-friendly mouse-click GUI.

Features

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   > 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     - Multiple regression coefficients     - Quantiles   > 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)     - All the analyses above can be carried out for arbitrary domains    

Future plans

> New statistical functions:     - Replication based Variance Estimation for non-analytic estimators, through the Delete‑A‑group Jackknife (DAGJK) technique: this will integrate the EVER package with the ReGenesees system > Enriched documentation:     - A self-contained user guide for the whole system is in progress and will be published as soon as possible

Get involved

For further information, interested people can contact the ReGenesees project leader at Istat: email zardetto@istat.it

Public administration reference

The ReGenesees project is being carried on at Istat - the Italian National Institute of Statistics