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Archive of posts filed under the Bayesian Statistics category.

If you get to the point of asking, just do it. But some difficulties do arise . . .

Nelson Villoria writes: I find the multilevel approach very useful for a problem I am dealing with, and I was wondering whether you could point me to some references about poolability tests for multilevel models. I am working with time series of cross sectional data and I want to test whether the data supports cross […]

Looking for Bayesian expertise in India, for the purpose of analysis of sarcoma trials

Prakash Nayak writes: I work as a musculoskeletal oncologist (surgeon) in Mumbai, India and am keen on sarcoma research. Sarcomas are rare disorders, and conventional frequentist analysis falls short of providing meaningful results for clinical application. I am thus keen on applying Bayesian analysis to a lot of trials performed with small numbers in this […]

Transitioning to Stan

Kevin Cartier writes: I’ve been happily using R for a number of years now and recently came across Stan. Looks big and powerful, so I’d like to pick an appropriate project and try it out. I wondered if you could point me to a link or document that goes into the motivation for this tool […]

“Schools of statistical thoughts are sometimes jokingly likened to religions. This analogy is not perfect—unlike religions, statistical methods have no supernatural content and make essentially no demands on our personal lives. Looking at the comparison from the other direction, it is possible to be agnostic, atheistic, or simply live one’s life without religion, but it is not really possible to do statistics without some philosophy.”

This bit is perhaps worth saying again, especially given the occasional trolling on the internet by people who disparage their ideological opponents by calling them “religious” . . . So here it is: Sometimes the choice of statistical philosophy is decided by convention or convenience. . . . In many settings, however, we have freedom […]

How literature is like statistical reasoning: Kosara on stories. Gelman and Basbøll on stories.

In “Story: A Definition,” visual analysis researcher Robert Kosara writes: A story ties facts together. There is a reason why this particular collection of facts is in this story, and the story gives you that reason. provides a narrative path through those facts. In other words, it guides the viewer/reader through the world, rather than just throwing […]

References (with code) for Bayesian hierarchical (multilevel) modeling and structural equation modeling

A student writes: I am new to Bayesian methods. While I am reading your book, I have some questions for you. I am interested in doing Bayesian hierarchical (multi-level) linear regression (e.g., random-intercept model) and Bayesian structural equation modeling (SEM)—for causality. Do you happen to know if I could find some articles, where authors could […]

Empirical implications of Empirical Implications of Theoretical Models

Robert Bloomfield writes: Most of the people in my field (accounting, which is basically applied economics and finance, leavened with psychology and organizational behavior) use ‘positive research methods’, which are typically described as coming to the data with a predefined theory, and using hypothesis testing to accept or reject the theory’s predictions. But a substantial […]

Win probabilities during a sporting event

Todd Schneider writes:

Teaching Bayesian applied statistics to graduate students in political science, sociology, public health, education, economics, . . .

One of the most satisfying experiences for an academic is when someone asks a question that you’ve already answered. This happened in the comments today. Daniel Gotthardt wrote: So for applied stat courses like for sociologists, political scientists, psychologists and maybe also for economics, what do we actually want to accomplish with our intro courses? […]

Those wacky anti-Bayesians used to be intimidating, but now they’re just pathetic

From 2006: Eric Archer forwarded this document by Nick Freemantle, “The Reverend Bayes—was he really a prophet?”, in the Journal of the Royal Society of Medicine: Does [Bayes's] contribution merit the enthusiasms of his followers? Or is his legacy overhyped? . . . First, Bayesians appear to have an absolute right to disapprove of any […]