**Paper**
This dataset contains the collected data and analysis script for:
###### de Fleurian, R., Blackwell, T., Ben-Tal, O., & Müllensiefen, D. (2017). Information-theoretic measures predict the human judgment of rhythm complexity. *Cognitive Science*, *41*(3), 800–813. doi: [10.1111/cogs.12347][1]
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**Corrigendum**
In Table 2, the values for excess entropy should be `0.174` and `0.378` instead of `0.208` and `0.361` (still non-significant once Bonferroni-corrected).
More details are available in the analysis script.
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**Data**
The data collected for this experiment is available as a `.csv` file [here][2]. The variables are as follows:
| Variable | Description
| -------- | -----------
|`msi_all` | Gold-MSI - General Sophistication
|`msi_perc` | Gold-MSI - Perceptual Abilities
|`msi_train` | Gold-MSI - Musical Training
|`apm` | Raven's Advanced Progressive Matrices - Set I
|`algo` | Generative algorithm (full names in [Appendix][3])
|`algo_id` | Generative algorithm, coded as 1-16
|`subseq` | Sub-sequence shown to participants for each algorithm
|`comp_H` | Shannon entropy
|`comp_h` | Entropy rate
|`comp_E` | Excess entropy
|`comp_T` | Transient information
|`comp_K` | Kolmogorov complexity
|`score` | 1 for correct, 0 for incorrect (correct answers in [Appendix][4])
|`easy` | Easiness rating on 1-7 scale
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**Analysis**
An analysis script written in `R` is available [here][5].
[1]: https://doi.org/10.1111/cogs.12347
[2]: https://osf.io/xwft7/
[3]: https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111/cogs.12347&file=cogs12347-sup-0001-Supinfo.pdf
[4]: https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111/cogs.12347&file=cogs12347-sup-0001-Supinfo.pdf
[5]: https://osf.io/mu3sa/
