Skip to content
Archive of posts filed under the Miscellaneous Statistics category.

Why do a within-person rather than a between-person experiment?

Zach Horne writes: A student of mine was presenting at the annual meeting of the Law and Society Association. She sent me this note after she gave her talk: I presented some research at LSA which used a within subject design. I got attacked during the Q&A session for using a within subjects design and […]

What if it’s never decorative gourd season?

If it rains, now we’ll change We’ll hold and save all of what came We won’t let it run away If it rains — Robert Forster I’ve been working recently as part of a team of statisticians based in Toronto on a big, complicated applied problem. One of the things about working on this project […]

Columbia statistics department is hiring!

Official announcement is below. Please please apply to these faculty and postdoc positions. We really need some people who do serious applied work, especially in social sciences. Obv these will be competitive, but please give it a shot, because we’d like to have some strong applied candidates in the mix for all of these positions. […]

Filling/emptying the half empty/full glass of profitable science: Different views on retiring versus retaining thresholds for statistical significance.

Unless you are new to this blog, you likely will know what this is about. Now, by profitable science in the title is meant repeatedly producing logically good explanations  which “through subjection to the test of experiment experiment, to lead to the avoidance of all surprise and to the establishment of a habit of positive […]

The dropout rate in his survey is over 60%. What should he do? I suggest MRP.

Alon Honig writes: I work for a cpg company that conducts longitudinal surveys for analysis of customer behavior. In particular they wanted to know how people are interacting with our product. Unfortunately the designers of these surveys put so many questions (100+) that the dropout rate (those that did not complete the survey) was over […]

Is Statistics Good for Democracy?

Above is the title of the talk I’ll be giving this Wednesday 5:30pm at the Math and Democracy Seminar downtown. Statistics is what people think math is. So maybe they should be calling it a “math and statistics seminar.” Anyway, here it is: This talk will be some mix of News You Can Use and […]

The devil’s in the details…and also in the broad strokes. Is this study ridiculous, or am I badly misjudging it?

This post is by Phil Price, not Andrew. Something caught my eye in a recent MIT Technology Review: an article in Nature Communications entitled ‘The greenhouse gas impacts of converting food production in England and Wales to organic methods.’ This is a subject that interests me, although I have no expertise in it whatsoever, so […]

Alternative titles for Regression and Other Stories

– A Book Called Regression – What to Expect When You’re Regressing Any other good silly ideas out there ???

“Causal Processes in Psychology Are Heterogeneous”

Niall Bolger sends along this article he wrote with Katherine Zee, Maya Rossignac-Milon, and Ran Hassin, which begins: All experimenters know that human and animal subjects do not respond uniformly to experimental treatments. Yet theories and findings in experimental psychology either ignore this causal effect heterogeneity or treat it as uninteresting error. This is the […]

Bayesian analysis of data collected sequentially: it’s easy, just include as predictors in the model any variables that go into the stopping rule.

Mark Palko writes: I remember you did something on the practice of continuing to add to the sample until significance was reached. I wanted to share it with some co-workers but I can’t seem to find it on your blog. Do you remember the one I am talking about? My reply: It’s here. There’s more […]

Perspectives

“Bellow began seeing a psychologist, a man named Paul Meehl.” Or as we might say it, “Meehl began seeing a patient, a writer named Saul Bellow.”

Statistician positions at RAND

Bonnie Ghosh-Dastidar writes: I am asking for your help in identifying qualified candidates for Ph.D. Statistician openings at the RAND Corporation with multiple location options (Santa Monica, CA, Washington, DC, Pittsburgh, PA, and Boston, MA). RAND was established almost 70 years ago to strengthen public policy through research and analysis. Over seven decades, our research […]

“Starting at the beginning again can be exhausting and stressful. But, opportunities are finally coming into focus . . .”

Ashley Steel writes: Walking away from science or walking away with science? This is an essay about career transitions and the value of statistical thinking in, perhaps, surprising places. It is written in hopes of opening a conversation. When my father, a kind and distinguished academic physician, gave me a chemistry set for my 12th […]

How to think scientifically about scientists’ proposals for fixing science

I kinda like this little article which I wrote a couple years ago while on the train from the airport. It will appear in the journal Socius. Here’s how it begins: Science is in crisis. Any doubt about this status has surely been been dispelled by the loud assurances to the contrary by various authority […]

What’s the p-value good for: I answer some questions.

Martin King writes: For a couple of decades (from about 1988 to 2006) I was employed as a support statistician, and became very interested in the p-value issue; hence my interest in your contribution to this debate. (I am not familiar with the p-value ‘reconciliation’ literature, as published after about 2005.) I would hugely appreciate […]

Glenn Shafer: “The Language of Betting as a Strategy for Statistical and Scientific Communication”

Glenn Shafer writes: I have joined the immense crowd writing about p-values. My proposal is to replace them with betting outcomes: the factor by which a bet against the hypothesis multiplies the money it risks. This addresses the desideratum you and Carlin identify: embrace all the uncertainty. No one will forget that the outcome of […]

BizStat: Modeling performance indicators for deals

Ben Hanowell writes: I’ve worked for tech companies for four years now. Most have a key performance indicator that seeks to measure the rate at which an event occurs. In the simplest case, think of the event as a one-off deal, say an attempt by a buy-side real estate agent to close a deal on […]

Jeff Leek: “Data science education as an economic and public health intervention – how statisticians can lead change in the world”

Jeff Leek from Johns Hopkins University is speaking in our statistics department seminar next week: Data science education as an economic and public health intervention – how statisticians can lead change in the world Time: 4:10pm Monday, October 7 Location: 903 School of Social Work Abstract: The data science revolution has led to massive new […]

Many perspectives on Deborah Mayo’s “Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars”

This is not new—these reviews appeared in slightly rawer form several months ago on the blog. After that, I reorganized the material slightly and sent to Harvard Data Science Review (motto: “A Microscopic, Telescopic, and Kaleidoscopic View of Data Science”) but unfortunately reached a reviewer who (a) didn’t like Mayo’s book, and (b) felt that […]

Controversies in the theory of measurement in mathematical psychology

We begin with this email from Guenter Trendler: On your blog you wrote: The replication crisis in social psychology (and science more generally) will not be solved by better statistics or by preregistered replications. It can only be solved by better measurement. Check this out: Measurement Theory, Psychology and the Revolution That Cannot Happen (pdf […]