A guide to robust statistical methods in neuroscience

Rand R. Wilcox provides data, code, and notebooks to reproduce all analyses and figures from the 2018 paper 'A Guide to Robust Statistical Methods in Neuroscience'. The package includes R functions and PDFs of all figures, along with extra notebooks describing simulations on statistical power and type I error. The work describes and illustrates improved methods for comparing groups and studying associations.

Use Cases

• Reproducing statistical analyses and figures from the 2018 paper based on the provided code and data.
• Comparing the performance of robust statistical methods for group comparisons as described in the paper.
• Studying associations between variables using the robust methods illustrated in the guide.
• Running extra simulations on statistical power and type I error based on the included notebooks.

Strengths

• Includes all code and data to fully reproduce the analyses and figures from the published paper.
• Provides extra notebooks describing simulations on power and type I error beyond the original publication.
• All figures are included in PDF format for direct reference.

Limitations

• Row count and dataset scale are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred from the paper and code.
• Last update date is unknown; freshness unverified.

Provenance

Source

Rand R. Wilcox, associated with the 2018 paper published in Current Protocols in Neuroscience.

Collection Method

Created to accompany the published methodological guide.