Alternatives to post‐processing posterior predictive p values

Prior-Posterior Predictive P-values

Understanding posterior p-values

Posterior predictive p-values do not in general have uniform distributions under the null hypothesis (except in the special case of pivotal test statistics) but instead tend to have distributions more concentrated near 0.5. From different perspectives, such nonuniform distributions have been portrayed as desirable (as reflecting an ability of vague prior distributions to nonetheless yield accur...

Detecting Positively Selected Amino Acid Sites Using Posterior Predictive P-Values

Identifying positively selected amino acid sites is an important approach for making inference about the function of proteins; an amino acid site that is undergoing positive selection is likely to play a key role in the function of the protein. We present a new Bayesian method for identifying positively selected amino acid sites and apply the method to a data set of hemagglutinin sequences from...

P-values, q-values and posterior probabilities for equivalence in genomics studies

Equivalence testing is of emerging importance in genomics studies but has hitherto been little studied in this content. In this paper, we define the notion of equivalence of gene expression and determine a ‘strength of evidence’ measure for gene equivalence. It is common practice in genome-wide studies to rank genes according to observed gene-specific P -values or adjusted P -values, which are ...

A farewell to P-values?

A recent paper in the medical literature by Sterne and Davey-Smith has focused attention on some of the problems of interpretation of significance/hypothesis tests; in particular, the meaning and status of P-values associated with these tests. What were these concerns: that the division of results into “significant” and “nonsignificant” according to a P-value = 0.05 was arbitrary and not in acc...