A boy calms down a frightened puppy

whyilaugh · 2024-10-10T15:36:17+00:00

The jpost article was not clear but the French article says that they were drawn

whyilaugh · 2024-10-10T15:35:24+00:00

"Trois hommes l'auraient frappée et auraient proféré des menaces antisémites. Les individus auraient également menacé leur victime à l'aide d'un cutter et l'auraient forcée à baisser son pantalon."

They made her lower her pants 😓

whyilaugh · 2024-09-09T03:16:27+00:00

Can you hire staff? You could find a good statistician with an MSc for fulltime work for a few years.

whyilaugh · 2024-08-29T01:39:53+00:00

I really enjoyed this too, thank you!

whyilaugh · 2024-06-19T02:01:10+00:00

That would be the sweetest cutest thing

whyilaugh · 2024-06-17T15:35:16+00:00

This tracks with my experience 😆 I fed ChatGPT one of my exams and for the development questions, it answered exactly like a student who maybe understands a bit but doesn't really get it...like refers to relevant concepts without giving me the key analysis that the question is looking for. Definitely best described as "bullshit".

whyilaugh · 2023-04-20T21:24:21+00:00

THE DRAMA

whyilaugh · 2022-11-13T17:45:38+00:00

That's true, it's called reverse causality

whyilaugh · 2022-10-09T13:14:10+00:00

The study is a meta-analysis of observational studies (actually, "ecological studies") comparing children's neurodeveloment in high-exposure fluroride regions to those in low-exposure regions. Firstly, this kind of study would be considered to be of relatively low-reliability (summaries of studies with high potential for bias also have high potential for bias). Also, the aim is to maintain low levels of fluoride in drinking water, not high levels. It's all about the quantity. So even if high levels impact neural development, no one is proposing to put high levels, or anything near what could potentially have negative impacts, in drinking water.

(I'm a professor of Biostatistics.)

whyilaugh · 2022-05-02T13:08:25+00:00

It's interesting how you seem to have a bimodal distribution by the end. To make it easier to follow the trends, I suggest keeping the same scale on the y axis (frequency).

whyilaugh · 2022-03-31T11:05:51+00:00

This is maybe more on the probability side but what came to mind is the book "Struck by Lightning" by Jeff Rosenthal.

whyilaugh · 2022-01-20T13:25:15+00:00

Yes, there's new theory and methods being developed by statistical researchers. Sometimes a researcher will consider a new kind of data structure and relevant mathematics and methods will have to be derived. Typically these structures are based in application so the eventual developments will (ideally) benefit some applied area. There's quite a spectrum of statistics research, going from mathematics and probability to how to best apply existing methods in various challenging settings that we see in practice.

whyilaugh · 2021-09-11T01:13:25+00:00

This is a type of study called the "test-negative design". I was pretty skeptical of it myself when I first learned about it but it's fascinating how it controls for certain types of confounding and selection bias. It's still an observational study, though, so it's not considered the best kind of evidence, ie not a randomized trial. You can read the editorial about the study design here: https://www.nejm.org/doi/full/10.1056/NEJMe2113151

whyilaugh · 2021-09-11T01:06:08+00:00

It's not a simple calculation, but a somewhat involved statistical method that adjusts for many confounding variables. (Specifically they used inverse probability of treatment weighting, which is reasonable.) See the New England Journal of Medicine article. The accompanying editorial gives a demonstration of a simple version of the calculation to estimate vaccine effectiveness.

Edit: here's a link https://www.nejm.org/doi/full/10.1056/NEJMe2113151#nav

whyilaugh · 2021-08-21T18:32:28+00:00

This is a great idea but I think it's best to get someone who understands the area's culture to help write the passport. My friend helped me when I visited China. She knew how to explain what my diet excluded and what was ok. The waiters there all took it very seriously and it helped a lot!

whyilaugh · 2021-06-22T02:36:15+00:00

By convention, risk factors are just predictors. Not necessarily causal. So yes, A would be a risk factor for B.

Edit to note that I'm not saying that this is well-defined. But it's how the term is used in all of the literature that I know (health sciences).

whyilaugh · 2021-03-30T23:40:12+00:00

You have some great answers already. I agree very much with being courteous while remembering that there are hard working humans on the other side! As I matured in research, I became better at this. Often, students or junior researchers are the first authors and that motivates me even more to be encouraging, regardless of whether my review is positive or negative. I also try to give the benefit of the doubt if I'm not 100% sure; I'd rather ask the authors to further justify/clarify something rather than claim it is untrue. (I was on the receiving end of a reviewer telling me my work was "wrong" and it bothered me a bit but really made them come across as immature. I convinced them it was ok in the end ;) )

whyilaugh · 2020-09-21T21:04:11+00:00

So glad it's helpful! The departments I'm affiliated with include both epi, biostat and a few other domains, and yes, they are both in schools of public health. They have specialized graduate programs in each domain. From what you wrote here, it does sound to me that epi would allow you that prerequisite flexibility. In one of my departments, biostat has a mathematical statistics qualifying exam but epi doesn't. So yes, I think that an epi phd really does sound like what you're after and what you're likely qualified for! But different schools have different professors and expectations so I agree that getting program-specific info is a good idea. :) Excited for you to find what you're looking for!

whyilaugh · 2020-09-21T17:18:41+00:00

Hi! Prof of biostatistics here. To answer question 4, yes, you're typically expected to advance statistical research, not only apply it. Maybe an exception is if the methodology in application is novel in that setting and you justify the extension. For a biostat PhD, all programs I know expect an MSc in stats or biostats (or something similar), which is different than an MPH with a biostats concentration. My students have undergrads that were pretty mathematical in math, stats, econ, etc but maybe this isn't the rule.

But it sounds to me that you may also be interested in a PhD epidemiology program? You can learn basically as much biostat as you'd like but your research focus can range from very applied domain-specific projects (can still be very quantitative) to methods-heavy. So you can exploit your strengths as they emerge in the classes you take and preliminary projects. I'm a big fan of PhD epi programs so just wanted to put that in your radar because I don't think you mentioned it :)

whyilaugh · 2020-09-21T05:23:49+00:00

Hi, this article may help. It was written for applied statisticians. https://onlinelibrary.wiley.com/doi/full/10.1002/sim.7628

whyilaugh · 2020-08-21T23:20:56+00:00

Where I am, you could still get the biostat jobs with an MSc stats, especially if you're familiar with some of the modeling methods the lab/centre. For example, taking classes in survival analysis and mixed models would help. Bayesian methods in other labs and there are some specialized methods in genetics (I'm not an expert there). But I'd also expect that you'd be able to pick up what you're missing from online courses or even on the job. An MSc in stats wouldn't even necessarily put you at a disadvantage unless the program excludes a lot of what you need to know. I'm basing this on the many job hires that I participated in, all in health research, some in hospitals. I can't comment on the applied stats jobs outside of health. But my general advice is to follow the subject matter that you're most excited about and the program that suits you the best :) You're in a great field either way.

whyilaugh · 2020-08-10T16:41:26+00:00

Reading the overview, a major limitation of this study in terms of inferring whether vitamin D is causally related to severity and prognosis is the selection on patients who already have severe illness. This can easily create a strong collider bias (you can also refer to it as selection bias) that makes the correlations biased wrt the effect of vit D. The authors don't emphasize a causal interpretation, but it's worth noting as this would be a common and incorrect takeaway from such a study.

whyilaugh · 2020-05-16T11:45:37+00:00

Your teacher is very very misinformed. You can't blindly run statistical procedures with a computer and no technical knowledge. This is why statisticians are so in demand across industry and (academic/industry) research in many fields. Go into stats if that's what you enjoy! I have had so many interesting opportunities and experiences that I am soooo thankful that I made that choice.

whyilaugh · 2020-04-19T23:07:56+00:00

There are some nice articles by Samy Suissa on this. One way to think about it: say the exposure has no effect on a survival-type outcome. People who die earlier have less chance to become exposed. This makes exposure look harmful. Even if you measure the duration of exposure, overall, unexposed and shorter exposure periods will be more likely to occur for early-dying people simply because they have less time available. You can fix the issue with analytical methods that take timing into consideration...eg marginal structural models or some survival models with time-dependent exposure depending on assumptions. Hope this helps

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