| RQube | |
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| Authors: | Jan Seifert, Patrick Britz |
| Latest Release: | 1.00.8.100; (2007-11-27) |
| Operating System: | Windows |
| License: | free software |
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Introduction to RQube
Randomization is a basic procedure in experimental design. Considered the importance of it, it is odd to say, that -- except for a few articles in parapsychological research -- the topic did not receive very much attention.
"Every finite symbol string is random under some nontrivial definitions of randomness.
Every finite symbol string is nonrandom under some nontrivial definitions of randomness."
These two paradoxical conclusions in Gilmore (1989, p. 339) underline the fact, that it might be worth the effort to consider the reasons of randomization and the principles of the process.
It is the purpose of RQube to provide several criteria to judge the quality of a random stimulus series. According to these criteria RQube generates as many series as you want. These may easily be implemented in your experiment control program.
Features
- RQube is not constrained to a single purpose of randomization. It randomizes according to various experimental needs.
- RQube is easy to use. It allows researchers to create stimulus sequences in an uncomplicated manner, to make sure, that the items in the sequence are well distributed, and to minimize predictability.
- RQube is fast. It is possible to assign an individual trial sequence to every subject.
- RQube output can easily be implemented in E-Prime and Presentation
- RQube has four different high quality random number generators implemented for effective and reliable randomization
- RQube provides output about the characteristics of the sequences. It is possible to introduce sequence characteristics as covariate/ continuous predictor into the ANOVA.
- The authors provide an extensive documentation along with the program.
