# Posts Tagged ‘ Bayesian statistics ’

## We got mooks

November 28, 2015
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Columbia University’s Data Science Institute is releasing some mooks, and I’m part of it. I’ll first give the official announcement and then share some of my thoughts. The official announcement: The Data Science Institute at Columbia University is excited to announce the launch of its first online-education series, Data Science and Analytics in Context, on […] The post We got mooks appeared first on Statistical Modeling, Causal Inference, and Social…

## Boston Stan meetup 1 Dec

November 25, 2015
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Here’s the announcement: Using Stan for variational inference, plus a couple lightning talks Dustin Tran will give a talk on using Stan for variational inference, then we’ll have a couple lightening (5 minute-ish) talks on projects. David Sparks will talk, I will talk about some of my work and we’re looking for 1-2 more volunteers. […] The post Boston Stan meetup 1 Dec appeared first on Statistical Modeling, Causal Inference,…

## I already know who will be president in 2016 but I’m not telling

November 23, 2015
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Nadia Hassan writes: One debate in political science right now concerns how the economy influences voters. Larry Bartels argues that Q14 and Q15 impact election outcomes the most. Doug Hibbs argues that all 4 years matter, with later growth being more important. Chris Wlezien claims that the first two years don’t influence elections but the […] The post I already know who will be president in 2016 but I’m not…

## 4 California faculty positions in Design-Based Statistical Inference in the Social Sciences

November 21, 2015
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This is really cool. The announcement comes from Joe Cummins: The University of California at Riverside is hiring 4 open rank positions in Design-Based Statistical Inference in the Social Sciences. I [Cummins] think this is a really exciting opportunity for researchers doing all kinds of applied social science statistical work, especially work that cuts across […] The post 4 California faculty positions in Design-Based Statistical Inference in the Social Sciences…

## Stan Puzzle 2: Distance Matrix Parameters

November 20, 2015
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$Stan Puzzle 2: Distance Matrix Parameters$

This puzzle comes in three parts. There are some hints at the end. Part I: Constrained Parameter Definition Define a Stan program with a transformed matrix parameter d that is constrained to be a K by K distance matrix. Recall that a distance matrix must satisfy the definition of a metric for all i, j: […] The post Stan Puzzle 2: Distance Matrix Parameters appeared first on Statistical Modeling, Causal…

## Pareto smoothed importance sampling and infinite variance (2nd ed)

November 18, 2015
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This post is by Aki Last week Xi’an blogged about an arXiv paper by Chatterjee and Diaconis which considers the proper sample size in an importance sampling setting with infinite variance. I commented Xi’an’s posting and the end result was my guest blog posting in Xi’an’s og. I made an additional figure below to summarise […] The post Pareto smoothed importance sampling and infinite variance (2nd ed) appeared first on…

## Inference from an intervention with many outcomes, not using “statistical significance”

November 14, 2015
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Kate Casey writes: I have been reading your papers “Type S error rates for classical…” and “Why We (Usually) Don’t Have to Worry…” with great interest and would be grateful for your views on the appropriateness of a potentially related application. I have a non-hierarchical dataset of 28 individuals who participated in a randomized control […] The post Inference from an intervention with many outcomes, not using “statistical significance” appeared…

## Bayesian Computing: Adventures on the Efficient Frontier

November 13, 2015
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That’s the title of my forthcoming talk at the Nips workshop at 9am on 12 Dec. The post Bayesian Computing: Adventures on the Efficient Frontier appeared first on Statistical Modeling, Causal Inference, and Social Science.

## Good value

November 10, 2015
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Earlier today we had our workshop on the Value of Information at the Ispor conference. I think it went well \$-\$ I counted about 80 people in the room, which was a big turnout, I think (I lost count three times, so I am not actually sure about the numbe...

## “Using prediction markets to estimate the reproducibility of scientific research”

November 9, 2015
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A reporter sent me this new paper by Anna Dreber, Thomas Pfeiffer, Johan Almenberg, Siri Isaksson, Brad Wilson, Yiling Chen, Brian Nosek, and Magnus Johannesson, which begins: Concerns about a lack of reproducibility of statistically significant results have recently been raised in many fields, and it has been argued that this lack comes at substantial […] The post “Using prediction markets to estimate the reproducibility of scientific research” appeared first…