Summary of survey software:
Generalized Estimation System (Systeme generalise d'estimation)
Types of designs that can be accommodated.
Stratified one stage element or cluster sampling; two-phase designs.
Types of estimands and statistical analyses that can be accommodated.
The focus of this software is on calibration estimation using generalized regression (GREG) estimator theory.
- Main functions are: calculation of sample design weights,
calculation of g-weights under a calibration approach, calculation of
calibration estimates, and calculation of synthetic estimates.
- Estimation of totals, averages, and ratios, for universe or domains.
- Auxiliary variables are used for estimation through the Generalized
Regression (GREG) approach. This framework permits a large family of
estimators including the traditional separate, combined and post-stratified
- Synthetic estimates can also be produced from auxiliary
information for each domain of interest.
Restrictions on number of variables or observations.
Size of data sets limited only by amount of available memory and size of
virtual memory (swap) file.
Primary methods used for variance estimation.
Jackknife or design-based formulae for the Generalized Regression
(GREG) estimator with Taylor linearization for non-linear parameters.
General description of the "feel" of the software.
GES is a SAS-based application, which runs under SAS (currently with Version 8).
A windows-type interface has been developed with SAS/AF.
Data must be either in SAS data set format or in ASCII form with fixed
field positions; GES can load data in ASCII form to a SAS data set.
Platforms on which the software can be run.
Platforms that have appropriate versions of SAS.
Availability, pricing and terms.
A site license allows installation on an unlimited number of machines.
A site license costs $30,000 (CDN) and $3,000 yearly maintenance fee.
All Web information on GES is in the process of being updated. Links will be
posted here when available.
- The principles underlying the development of GES are discussed in
the following article:
V. Estevao, M.A. Hidiroglou, and C.E. Sarndal, "Methodological
Principles for a Generalized Estimation System at Statistics Canada,"
Journal of Official Statistics, 11, 181-204 (1995).
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