Follow-up to the statement on p-values by ASA

The American Statistical Association Says [Mostly] No to p-values Norman Matloff has published a new post after receiving criticism and comments about stating “The ASA says No to p-values” in his post I wrote about some days ago. He defends his interpretation in this new post. However, I think, the interpretation of  the statement in a context different from the “Big data” field to which he is used to does not need to always be “Says No to p-values” but instead in many cases could be “Use p-values to assess the strength of the evidence and nothing else”.  However, “tests” with binary outcomes on probabilities that are essentially continuous, will always be based on an arbitrary threshold and discard a great deal of information. Consequently to me using as suggested by Norman Matloff  “assess” in place of “test” makes a lot of sense. The new post is at https://matloff.wordpress.com/2016/03/09/further-comments-on-the-asa-manifesto/ “Itʹs Not The P-valuesʹ Fault” Joint post by Yoav Benjamini and Tal Galili. The post highlights points raised by Yoav in his official response to the ASA statement… Source: It’s Not The P-values’ Fault – Reflections On The Recent ASA Statement (+relevant R Resources) | R-statistics Blog P-values: the Continuing Saga I highly recommend the blog post by Yoav Benjamini and…

Continue reading

Rigor and Reproducibility

The NIH (USA, National Institutes of Health) has opened a new web site on the subject, which although focused on Biomedical research, provides a good account of current trends and problems, how to overcome them and guidelines that could be easily adapted for the rest of the Biosciences including UV-related research on plants. Rigor and Reproducibility  at NIH (USA) I propose that we follow the example of the Biophysical Society and write our own version of the guidelines adapted to the needs and problems of Plant UV-photobiology. Please give feedback on this idea by leaving a reply or comment.

Continue reading