Category: Sociology

“Retire Statistical Significance”: The discussion.

So, the paper by Valentin Amrhein, Sander Greenland, and Blake McShane that we discussed a few weeks ago has just appeared online as a comment piece in Nature, along with a letter with hundreds (or is it thousands?) of supporting signatures. Following the first circulation of that article, the authors of that article and some […]

One more reason I hate letters of recommendation

Recently I reviewed a bunch of good reasons to remove letters of recommendation when evaluating candidates for jobs or scholarships. Today I was at a meeting and thought of one more issue. Letters of recommendation are not merely a noisy communication channel; they’re also a biased channel. The problem is that letter writers are strategic: […]

Our hypotheses are not just falsifiable; they’re actually false.

Everybody’s talkin bout Popper, Lakatos, etc. I think they’re great. Falsificationist Bayes, all the way, man! But there’s something we need to be careful about. All the statistical hypotheses we ever make are false. That is, if a hypothesis becomes specific enough to make (probabilistic) predictions, we know that with enough data we will be […]

New estimates of the effects of public preschool

Tom Daula writes: You blogged about Heckman and the two 1970s preschool studies a year ago here and here. Apparently there are two papers on a long-term study of Tennessee’s preschool program. In case you had an independent interest in the topic, a summary of the most recent paper is here, and the paywalled paper […]

The bullshit asymmetry principle

Jordan Anaya writes, “We talk about this concept a lot, I didn’t realize there was a name for it.” From the wikipedia entry: Publicly formulated the first time in January 2013 by Alberto Brandolini, an Italian programmer, the bullshit asymmetry principle (also known as Brandolini’s law) states that: The amount of energy needed to refute […]

Storytelling: What’s it good for?

A story can be an effective way to send a message. Anna Clemens explains: Why are stories so powerful? To answer this, we have to go back at least 100,000 years. This is when humans started to speak. For the following roughly 94,000 years, we could only use spoken words to communicate. Stories helped us […]

Did she really live 122 years?

Even more famous than “the Japanese dude who won the hot dog eating contest” is “the French lady who lived to be 122 years old.” But did she really? Paul Campos writes: Here’s a statistical series, laying out various points along the 100 longest known durations of a particular event, of which there are billions […]

The post Did she really live 122 years? appeared first on Statistical Modeling, Causal Inference, and Social Science.

What to do when you read a paper and it’s full of errors and the author won’t share the data or be open about the analysis?

Someone writes: I would like to ask you for an advice regarding obtaining data for reanalysis purposes from an author who has multiple papers with statistical errors and doesn’t want to share the data. Recently, I reviewed a paper that included numbers that had some of the reported statistics that were mathematically impossible. As the […]

The post What to do when you read a paper and it’s full of errors and the author won’t share the data or be open about the analysis? appeared first on Statistical Modeling, Causal Inference, and Social Science.

What to do when you read a paper and it’s full of errors and the author won’t share the data or be open about the analysis?

Someone writes: I would like to ask you for an advice regarding obtaining data for reanalysis purposes from an author who has multiple papers with statistical errors and doesn’t want to share the data. Recently, I reviewed a paper that included numbers that had some of the reported statistics that were mathematically impossible. As the […]

The post What to do when you read a paper and it’s full of errors and the author won’t share the data or be open about the analysis? appeared first on Statistical Modeling, Causal Inference, and Social Science.