P values: from suggestion to superstition

P values: from suggestion to superstition

A threshold probability value of 'p≤0.05' is commonly used in clinical investigations to indicate statistical significance. To allow clinicians to better understand evidence generated by research studies, this review defines the p value, summarizes the historical origins of the p value approach to hypothesis testing, describes various applications of p≤0.05 in the context of clinical research a...

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...

From P-Values to Objective Probabilities in Assessing Medical Treatments

The assessment of the effectiveness of a treatment in a clinical trial, depends on calculating p-values. However, p-values are only indirect and partial indicators of a genuine effect. Particularly in situations where publication bias is very likely, assessment using a p-value of 0.05 may not be sufficiently cautious. In other situations it seems reasonable to believe that assessment based on p...

Superstition in the pigeon.

Values Suggestion in Mixed Integer Programming by Machine Learning Algorithm

Constraint logic programming is a framework for modeling constraint satisfaction and optimization problems. To use the techniques of constraint programming eeciently in applications software some knowledge and experience of the problem domain is demanded. In order to get some of the problem domain knowledge we investigated usage of some machine learning methods in the eld of constraint logic pr...