One of the unique features of Bayesian statistical and computational modelling is the prior distribution. A prior distribution is both conceptually and formally necessary to do any sort of Bayesian modelling. If we are estimating the values of model parameters (e.g., regression coefficients), we do this by updating our prior beliefs about the parameter values […]
Statistics and Methodology
I see four benefits to the use of Bayesian inference: Inclusion of prior information. Regularization. Handling models with many parameters or latent variables. Propagation of uncertainty. Another selling point is a purported logical coherence – but I don’t really buy that argument so I’ll forget that, just as I’ll also set aside philosophical objections against […]
The #BayesInPsych Digital Event kicked off yesterday and as the leading Guest Editor of the special issue of Psychonomic Bulletin & Review, I take this opportunity to provide more context for this week’s posts. The simple act of deciding which among competing theories is most likely—or which is most supported by the data—is the most […]
Your brilliant PhD student ran an experiment last week that investigated whether chanting the words “unicorns, Brexit, fairies” repeatedly every morning before dawn raises people’s estimates of the likelihood that they will win the next lottery in comparison to a control group that instead chants “reality, reality, reality”. The manipulation seems to have worked, as […]
Is a picture necessarily worth a thousand words? Do bilinguals always find some grammatical features in their second language to be more difficult than native speakers of that language? Is the Stroop effect necessarily larger when the task is to name the color ink of a color word than when the task is to read […]
Replication and reanalysis of old data is critical to doing good science. We have discussed at various points how to increase the replicability of studies (e.g. here, here, here, and here), and have covered a few meta-analyses (here, here). Maybe it is because technology is constantly changing, and because we forget where we leave files […]
The scientific process relies on the ability to replicate findings. This is as true in psychology as in any other discipline. If findings can be reliably replicated, researchers can draw theory-changing conclusions from relatively few data points. But all is not well, and psychology has been dealing with the famous “replication crisis.” Recently a very […]
“Progress is not possible without deviation.” — Frank Zappa The ways by which psychological science deals with methodological problems are many. There are bottom-up approaches such as peer-reviewed papers and workshops given by methodologists who advocate particular types of changes. There are also top-down approaches, such as funding agencies requiring data sharing or journals requiring […]
Since Herb Clark published his famous “Language as a fixed effect fallacy” in 1973, there has been a slow realization that standard techniques, such as ANOVA, are the wrong tools for the jobs that most psychologists tackle. The basic problem is that most psychological questions involve generalization beyond a sample of people and beyond a […]
This is the first in a series of posts on online data-collection. The popularity of collecting behavioral data online continues to rise. The reasons are many: ease of getting large numbers of participants, relatively low cost, and access to a more diverse population. Early concerns that online data collection is inherently unreliable are gradually evaporating, […]