Tools
Random generation of auxiliary variables
In Schouten (2015, Discussion paper 2015-15, CBS, Den Haag, The Netherlands) and Schouten (2017, JRSS series B), R-indicators and coefficients of variation (CV) are evaluated under random generation of auxiliary variables. A framework is presented for various variable-generating distributions and the expected amount of explained variation is derived. In the 2017 JRSSB paper, a data set extracted from the CentERdata LISS-panel, see www.lissdata.nl, features as an example. The data set and R code to reproduce the example are available here. The SPSS file contains a codebook.
You can download the following files:
Computation of R-indicators - Version 2.1
An extended version of the RISQ 2 code in SAS and R was released at September 14, 2015. RISQ 2.1 estimates partial CV at the variable-level and at the category level. Furthermore, it approximates standard errors for the overall CV and partial CV. The manual is extended and discusses the new indicators.
You can download the following files:
- The manual RISQ Manual Version 2.1
- The SAS code (R-indicators Version 2.0.(SAS)
- The R code (R-indicators Version 2.0 (R)
Computation of R-indicators - Version 2.0
This is the new version of the RISQ code in SAS and R. It was released in February, 2014. RISQ 2 includes standard error approximations for all indicators, and it also has the coefficient of variation. Furthermore, bias adjustment has slightly changed with respect to version 1 of the code. The use of the functions is explained and illustrated in the manual.
You can download the following files:
- The manual RISQ Manual Version 2
- The SAS code (R-indicators Version 2.0.(SAS)
- The R code (R-indicators Version 2.0 (R)
Computation of R-indicators - Version 1.0
The computation of R-indicators and partial R-indicators are implemented in SAS and R. The code for both SAS and R can be downloaded. The code contains all functions needed to compute:
- R-indicators
- Unconditional partial R-indicators at the variable level and the category level
- Conditional partial R-indicators at the variable level and the category level
- The use of the functions is explained and illustrated in the manual.
You can download the following files:
- The manual (RISQ Deliverable 12.1)
- The SAS code (RISQ_R-indicators_v1.0.sas)
- The R code (RISQ_R-indicators_v1.0.r)
- The SPSS test data set used in the manual (RISQ-test.sav)
The program Cockpit
Cockpit is a software tool that demonstrates the graphical possibilities of survey response analysis with R-indicators.Cockpit can generate in ann interactive way the following plots:
- Box plots of response probabilities for each category of an auxiliary variables
- Bar plots of unconditional R-indicators for sets of auxiliary variables
- Bar plots of unconditional R-indicators for the categories of an auxiliary variable
- Bar plots of conditional R-indicators for sets of auxiliary variables
- Bar plots of conditional R-indicators for the categories of an auxiliary variable
Cockpit requires a data file and a metadata file. Such files can be generated from SPSS or Stata files with R scripts that are included in the package. Also included is a demonstration data set with data form a Statistics Netherlands survey.
It should be noted that Cockpit is just a demonstration tool and not a production tool. No bias correction is carried out in the computations of the various R-indicators.
A zip-file can be downloaded. This contains the following files:
- cockpit.exe (the program itself, non-installation required)
- cockpit.pdf (the cockpit manual)
- gps.rin (sample metadata file)
- gps.dat (sample data file)
- export-spss.r (R-script to export data and metadata from SPSS to Cockpit).
- export-stata.r (R-script to export data and metadata from Stata to Cockpit).