P values and Multiple Comparison Procedures: Some resources

[R_cubed]

I discovered an interesting video from the NISS channel on Youtube related to the use of p values in decision making that might be of interest.

NISS Webinar Hosts Third Webinar on the Use of p-values for Making Decisions

The Use of p-Values in Making Decisions: A Third NISS Webinar - May, 2020

Digging Deeper from the Radical to the Reasoned: p-value Alternatives Offered...

Digging Deeper Into p-values: NISS Webinar Follow-up with Three Authors - November, 2020

NISS Webinar Reviews Alternatives to the Traditional p-value to a Packed House!

NISS Webinar: Alternatives to the Traditional p-value - May, 2020

Related Threads

Author Checklist

Statistical Problems to Document and to Avoid Checklist for Authors References | Ten Simple Rules | Checklist to Avoid p-Hacking | Research Reliability and Publishing | Guidelines for Reporting of Statistics | Guidelines for Figures and Tables | Statistical Myths | Video | Common Pitfalls This list is not all-inclusive, and nominations for additional entries are welcomed. The list is not meant to imply that a lead author should wait until the end to correct statistical errors, especially w…

Reference Collection to push back against "Common Statistical Myths"

The following threads had a discussion of this issue. It seems like it could fall under the p value misconception heading, but I think it deserves a section on its own. I think the Bayesian POV provides a framework for guidance on this. @Sander provided references to Bayesian justifications for adjustment. Some of his own writing on the issue: I posted a few references in the context of clinical trials in this thread: The following is as close to a complete theory of MCPs as we are …

https://link.springer.com/article/10.1007/s11229-021-03276-4

@Sander posted a brief review of the Mark Rubin paper (link immediately above) here:

Review of: "When to Adjust Alpha During Multiple Testing"