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They’re also not really hyping up or focusing on those subgroup differences… it’s not mentioned in the abstract, nor at any point in the conclusions, from what I can see. Their focus is on the result that laptops decreased performance overall, which nobody seems to have a problem with.

The WaPo blog post is another matter; the writer there zeros in on the subgroup comparisons as the most interesting part of the paper, and fails to acknowledge that the comparisons aren’t statistically significant. It’s not really clear whether the target of Andrew’s criticism is the blogger or the original authors, but to the extent it’s aimed at the bloggers I think it’s well-founded.

One could also argue that the blogger’s error represents a failure of communication on the part of the study authors. Personally I think that’s a little too harsh, in this case.

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May 25, 2016 at 7:25 pm

I disagree. Sure, I agree that it’s better for researchers to give caveats if they’re going to interpret what could be noise, but the problem here is selection. If you want to interpret non-significant comparisons, you should look at all of them. To select a subset of comparisons based on a difference between significant and non-significant is just noisy. To put it another way, think of all the other non-significant differences in the data. Don’t they deserve interpretation too. If you let your choice of what to interpret and what to conclude be driven by comparisons of significant to non-significant, you’re chasing noise.

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Okay, that’s fair. I still think the original paper explicitly demonstrates an understanding that, “the difference between significant and not significant is not itself statistically significant,” so I don’t think they chose to report those particular comparisons for that reason. But I guess it doesn’t really matter whether their selections were motivated by a misunderstanding of statistics or by some other arbitrary criteria (e.g., perhaps the non-significant differences they reported were more interesting than the ones they didn’t); there’s an overinterpretation problem either way.

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The statement, “What’s interesting is that the smartest students seemed to be harmed the most” (which was made in the news article, not in the research article) is a comparison between different groups of students. The comparison could be expressed as (A2 – A1) – (B2 – B1). But the conclusion is based on A2-A1 being statistically significant, and B2-B1 being not statistically significant. This is an error.

Similarly, the statement quoted above, “These results are nearly identical,” makes the statistical error taking a non-significant difference which, just by chance, happens to be very close to zero in the sample, and claiming this maps only to a small difference in the population.

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Yes … if p = 0.05 means that 5% of the time you will get those results, then it ought to be a uniform distribution: 10% of the time you will get p = 0.1, etc.

Point is not so much that the distribution is expected, more that I hadn’t thought much about what distribution to expect until now. And that distribution is very non-gaussian.

Reply to this comment
May 25, 2016 at 4:46 pm

Tom, the sort of simulations that you ran are great for exploring the nature of P-values and for tuning your intuition. You might be interested in the relationship between P-values and likelihood functions that can be exposed by them .

Reply to this comment
May 25, 2016 at 10:24 pm


Reply to this comment
May 25, 2016 at 2:09 pm

I think my comment earlier disappears, so here goes attempt no. 2:

With the caveat that I’ve only glanced at the paper, I don’t see how your criticism is valid. It’s clear from the abstract and tables that it is *not* the case that the authors only find an effect if they divide their subjects into particular groups. Rather, there’s notably worse performance by the laptops-in-class group; again, this is the claim that’s made in the abstract. *In addition,* one can look at sub-groups and poke around — this seems to be a minor point of the paper.

Furthermore, even if one argues that they shouldn’t be looking at sub-groups, your criticism that the authors make the mistake that “The difference between “significant” and ‘not significant’ is not itself statistically significant” seems wrong. It’s not that they are comparing the different GRE/ACT-scoring groups with each other, but rather comparing e.g. high-level students in laptop-classes with high-level students in no-laptop classes. Your simple adding-the-variance calculation isn’t actually adding the relevant variances. (It’s possible my quick reading is incorrect; feel free to correct me.)

Overall, your characterization of this seems rather irresponsible.

Reply to this comment
May 25, 2016 at 5:09 pm

The paper does report on differences between the ‘smart’ and ‘poor’ student subgroups, and it offers a few lines of speculation for what might be driving those differences (other than noise). That said, they also acknowledge that, “the point estimates […] are statistically indistinguishable, so these could be chance findings.” In essence they’re saying, “this could be noise, but if it’s not, here’s what we think might be going on.” I see no problem with that.

Amos D. Wenger, already in Lancaster County at the time, was leading almost-but-not-quite-revival meetings that gained greater attention and following after the accident. Young people started to look at baptism and joining the church at a younger age—as opposed to waiting for marriage. Indeed, baptismal classes were larger than normal that summer, with about five hundred young people becoming church members. The impact of this was felt long through the conference on the account of the energy the young people brought in.

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But there is also a perhaps less important impact of this story. In 1882, Sarah Lucinda Hershey made a hair picture of herself and her siblings—including Barbara Hershey. It is a fascinating thing—a punch card background, neatly framed in wood with the first initial carefully stitched below each of the thirteen locks of hair. Each lock of hair, some braided, others loosely gathered, is neatly bundled with ribbon. In the middle, “A Token of Love” with cross-stitched flowers with silk other and feathers as finishing touches. The piece came to the Society’s collection through a non-Mennonite antique dealer, and little is known during the time period between its construction and its purchase by the Society. 3

I am looking for other similar hair memorials, in any form, that have Mennonite connections to provide comparative analysis. If you know of one, please connect with me through the Lancaster Mennonite Historical Society.

Posted on by Ben Goossen

“Not all the Jews were bad,” a widely respected Mennonite born in interwar Ukraine told me recently, “even though they started the [Bolshevik] Revolution. My father had good Jewish friends.” This statement is classically anti-Semitic. It falsely conflates communism with Judaism, while using the excuse of having a few Jewish friends to mask an implied belief that Jews in general were bad. At least as importantly, my conversation partner’s words reveal how people who do not consider themselves racist or anti-Semitic can still propagate harmful myths.

New scholarship and ongoing public discussion about the historic entanglement of tens of thousands of Mennonites on three continents with Nazism and the Holocaust during the 1930s and 1940s has yielded productive conversation regarding how present-day Anabaptists can and should respond to this history, as well as calls for further discussion . At the same time, some church-affiliated periodicals have printed articles, letters, and reviews that propagate troubling interpretations of Mennonite-Nazi connections, including anti-Semitic tropes.

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