Hooper [1] defends using P-values to answer the question, “do we think there is an effect at all.” But what advantage is there in viewing measurable phenomena as a dichotomy? The P-value’s role in significance testing only fosters this unfortunate dichotomous thinking. Quantitative thinking is preferable [2]. Although one could argue that a zero effect is qualitatively different from other values, one cannot distinguish zero from values close to it. It makes far more sense to consider zero on an equal footing with all other possible effect values. The question for the investigator ought to be “what is the best estimate of effect given the data in hand?” [3].
