Posts Tagged ‘ Bayesian statistics ’

“If you’re not using a proper, informative prior, you’re leaving money on the table.”

November 21, 2014
By

Well put, Rob Weiss. This is not to say that one must always use an informative prior; oftentimes it can make sense to throw away some information for reasons of convenience. But it’s good to remember that, if you do use a noninformative prior, ...

Read more »

Soil Scientists Seeking Super Model

November 20, 2014
By
Soil Scientists Seeking Super Model

I (Bob) spent last weekend at Biosphere 2, collaborating with soil carbon biogeochemists on a “super model.” Model combination and expansion The biogeochemists (three sciences in one!) have developed hundreds of competing models and the goal of the workshop was to kick off some projects on putting some of them together intos wholes that are […] The post Soil Scientists Seeking Super Model appeared first on Statistical Modeling, Causal Inference,…

Read more »

Secretary

November 18, 2014
By
Secretary

Second time lucky, I've just been elected Secretary of the International Society for Bayesian Analysis (ISBA) Section on Biostatistics and Pharmaceutical Statistics. The aim of this specialised section of ISBA is to help network and federate under...

Read more »

Question about data mining bias in finance

November 16, 2014
By

Finance professor Ravi Sastry writes: Let’s say we have N vectors of data, {y_1,y_2,…,y_N}. Each is used as the dependent variable in a series of otherwise identical OLS regressions, yielding t-statistics on some parameter of interest, theta: {t_1,t_2,…,t_N}. The maximum t-stat is denoted t_n*, and the corresponding data are y_n*. These are reported publicly, as […] The post Question about data mining bias in finance appeared first on Statistical Modeling,…

Read more »

Best job ever

November 14, 2014
By
Best job ever

The job advert for the postdoc position in our MRC-funded project on the Regression Discontinuity Design is finally out.Aidan has done a fantastic job in his little over a year in the position, but he's now moved to a lectureship in our department...

Read more »

“The Statistical Crisis in Science”: My talk in the psychology department Monday 17 Nov at noon

November 14, 2014
By

Monday 17 Nov at 12:10pm in Schermerhorn room 200B, Columbia University: Top journals in psychology routinely publish ridiculous, scientifically implausible claims, justified based on “p < 0.05.” And this in turn calls into question all sorts of more plausible, but not necessarily true, claims, that are supported by this same sort of evidence. To put […] The post “The Statistical Crisis in Science”: My talk in the psychology department Monday…

Read more »

The history of MRP highlights some differences between political science and epidemiology

November 11, 2014
By

Responding to a comment from Thomas Lumley (who asked why MRP estimates often seem to appear without any standard errors), I wrote: In political science, MRP always seems accompanied by uncertainty estimates. However, when lots of things are being displayed at once, it’s not always easy to show uncertainty, and in many cases I simply […] The post The history of MRP highlights some differences between political science and epidemiology…

Read more »

“The Firth bias correction, penalization, and weakly informative priors: A case for log-F priors in logistic and related regressions”

November 5, 2014
By

Sander Greenland sent me this paper that he wrote with Mohammad Ali Mansournia, which discusses possible penalty functions for penalized maximum likelihood or, equivalently, possible prior distributions for Bayesian posterior mode estimation, in the context of logistic regression. Greenland and Mansournia write: We consider some questions that arise when considering alternative penalties . . . […] The post “The Firth bias correction, penalization, and weakly informative priors: A case for…

Read more »

My talk today at the University of Michigan, 4pm at the Institute for Social Research

November 3, 2014
By

Generalizing from sample to population Andrew Gelman, Department of Statistics, Columbia University We’ve been hearing a lot about “data” recently, but data are generally a means to an end, with the goal being to learn about some population of interest. How do we generalize from sample to population? The process seems a bit mysterious, especially […] The post My talk today at the University of Michigan, 4pm at the Institute…

Read more »

"Football"… I mean "soccer"… I mean "football"…

October 29, 2014
By

A couple of weeks ago, I was contacted by Daniel Weitzenfeld $-$ a Chicago freelance data scientist (his own definition). Daniel got interested in modelling sports results and googled our football paper $-$ in his post here, he jokes that, be...

Read more »


Subscribe

Email:

  Subscribe