Frequentism vs. Bayesianism: Pick a side
Posted on StatsJobs.com March 11, 2015
Basic and Applied Social Psychology (BASP) has banned the use of null hypothesis significance testing procedure (NHSTP). The editorial making the announcement is full of evocative language about having to “remove all vestiges of the NHSTP” from manuscripts before publication, criticising “the stultified structure of NHSTP thinking”, and liberating psychological research from the “crutch of NHSTP”. They’re down on confidence intervals as well and, while no direct alternative is proposed, Bayesian analysis gets a Highly Commended. If that sounds like a battle line being drawn in another epistemological paradigm war, this might be a good time to pick a side. Are you a Frequentifier or a Bayesianite?
It’s probably about probability
The Frequentist approach calculates the probability of A based on the number of times it occurs out of the number of opportunities for it to occur, P(A) = n/N. Because it’s impossible to observe every opportunity for A to occur, a sample of observations is selected, which means that Frequentist analysis always includes sampling error, and measures the relative probability of an event. The common perception is that it gives the probability of an observation being true. Another misconception is that probability is some proxy for replicability. However, the probability of exact replication of a reported result is no better than chance (50%) even where p < .001. Frequentist analysis often also reports the effect size, which indicates the proportion of variance of a dependent variable associated with levels of an independent variable. Effect size can be measured using η2, Cohen’s d, or ω2, depending on cell sizes and so on, and is useful in interpreting analysis.
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