Posts Tagged ‘ Bayesian statistics ’

Quick update

May 22, 2017
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Quick update

This is going to be a very short post. I've been again following the latest polls and have updated my election forecast model $-$ nothing has changed in the general structure, only new data coming as the campaigns evolve.The dynamic forecast (which con...

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Some natural solutions to the p-value communication problem—and why they won’t work.

May 21, 2017
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Some natural solutions to the p-value communication problem—and why they won’t work.

John Carlin and I write: It is well known that even experienced scientists routinely misinterpret p-values in all sorts of ways, including confusion of statistical and practical significance, treating non-rejection as acceptance of the null hypothesis, and interpreting the p-value as some sort of replication probability or as the posterior probability that the null hypothesis […] The post Some natural solutions to the p-value communication problem—and why they won’t work.…

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A continuous hinge function for statistical modeling

May 19, 2017
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A continuous hinge function for statistical modeling

This comes up sometimes in my applied work: I want a continuous “hinge function,” something like the red curve above, connecting two straight lines in a smooth way. Why not include the sharp corner (in this case, the function y=-0.5*x if x0)? Two reasons. First, computation: Hamiltonian Monte Carlo can trip on discontinuities. Second, I […] The post A continuous hinge function for statistical modeling appeared first on Statistical Modeling,…

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Causal inference using Bayesian additive regression trees: some questions and answers

May 18, 2017
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[cat picture] Rachael Meager writes: We’re working on a policy analysis project. Last year we spoke about individual treatment effects, which is the direction we want to go in. At the time you suggested BART [Bayesian additive regression trees; these are not averages of tree models as are usually set up; rather, the key is […] The post Causal inference using Bayesian additive regression trees: some questions and answers appeared…

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Using Stan for week-by-week updating of estimated soccer team abilites

May 17, 2017
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Using Stan for week-by-week updating of estimated soccer team abilites

Milad Kharratzadeh shares this analysis of the English Premier League during last year’s famous season. He fit a Bayesian model using Stan, and the R markdown file is here. The analysis has three interesting features: 1. Team ability is allowed to continuously vary throughout the season; thus, once the season is over, you can see […] The post Using Stan for week-by-week updating of estimated soccer team abilites appeared first…

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Through time & space

May 15, 2017
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Through time & space

I've continued to fill in the data from the polls and re-run the model for the next UK general election. I think the dynamic element is interesting in principle, mainly because of how the data from the most recent polls could be weighed differently tha...

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Splines in Stan! (including priors that enforce smoothness)

May 13, 2017
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Splines in Stan! (including priors that enforce smoothness)

Milad Kharratzadeh shares a new case study. This could be useful to a lot of people. And here’s the markdown file with every last bit of R and Stan code. Just for example, here’s the last section of the document, which shows how to simulate the data and fit the model graphed above: Location of […] The post Splines in Stan! (including priors that enforce smoothness) appeared first on Statistical…

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Accounting for variation and uncertainty

May 12, 2017
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[cat picture] Yesterday I gave a list of the questions they’re asking me when I speak at the Journal of Accounting Research Conference. All kidding aside, I think that a conference of accountants is the perfect setting for a discussion of of research integrity, as accounting is all about setting up institutions to enable trust. […] The post Accounting for variation and uncertainty appeared first on Statistical Modeling, Causal Inference,…

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How to interpret “p = .06” in situations where you really really want the treatment to work?

May 11, 2017
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How to interpret “p = .06” in situations where you really really want the treatment to work?

We’ve spent a lot of time during the past few years discussing the difficulty of interpreting “p less than .05” results from noisy studies. Standard practice is to just take the point estimate and confidence interval, but this is in general wrong in that it overestimates effect size (type M error) and can get the […] The post How to interpret “p = .06” in situations where you really really…

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A completely reasonable-sounding statement with which I strongly disagree

May 5, 2017
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From a couple years ago: In the context of a listserv discussion about replication in psychology experiments, someone wrote: The current best estimate of the effect size is somewhere in between the original study and the replication’s reported value. This conciliatory, split-the-difference statement sounds reasonable, and it might well represent good politics in the context […] The post A completely reasonable-sounding statement with which I strongly disagree appeared first on…

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