What does R-sw Tradeoff do?
- it allows generating a PCS design or check the properties of an existing design;
- it performs individual hierarchical Bayes (HB) estimation of PCS data;
- it performs individual traditional logit estimation of PCS data.
Details:
- no minimum number of tasks for hierarchical Bayes estimation;
- all respondents must evaluate the same number of paired tasks;
- it is possible to ask respondents to indicate the strength of the preference (left profile strongly preferred, slightly preferred, etc.) The model works with 3, 5, 7, 9, or 11 points in the scale, although respondents might not necessarily be exposed to the (central) neutral point;
- the user can change the hierarchical Bayes (HB) parameters (number of Markov Chain Monte Carlo draws and the Markov Chain Monte Carlo thinning parameter);
- the outcomes are individual raw utilities (coefficients) for each item included in the experimental design; they are on a scale [0:100];
- data can be easily imported and outcomes can be exported as CSV/text files.
Support, Manual and Examples:
- technical support and statistical consulting is available free of charge (within reasonable limits);
- an ‘html’ manual is provided with a detailed description of all available functions;
- full working examples are provided to help the User to become familiar with the package. These examples can be easily adapted by the User for new projects.
Note: this is a pure design and analysis tool, therefore data must be collected through an external source (such as a CAWI, CAPI or PAPI system).