I came across this great post at the Mind Hacks blog by Vaughan Bell, which is about how we talk about psychiatric diseases, their diagnosis and criticising their nature.
Debating the validity of diagnoses is a good thing. In fact, it’s essential we do it. Lots of DSM diagnoses, as I’ve argued before, poorly predict outcome, and sometimes barely hang together conceptually. But there is no general criticism that applies to all psychiatric diagnosis.
His final paragraph touches something which I also discuss in my course on Psychological Assessment and Decisions:
Finally, I think we’d be better off if we treated diagnoses more like tools, and less like ideologies. They may be more or less helpful in different situations, and at different times, and for different people, and we should strive to ensure a range of options are available to people who need them, both diagnostic and non-diagnostic.
Diagnoses are a man-made concept that can be helpful in order to make decisions and study the subject. Vaughan makes a great case for how this is true for both mental and somatic conditions.
I came across this interesting article at The Thesis Whisperer blog. It starts with the hypothesis being an academic is similar to “running a small, not very profitable business”. This is mainly down to two problems:
Problem one: There are a lot of opportunities that could turn into nothing, so it’s best to say yes to everything and deal with the possible overwork problem later.
Problem two: Since (outside of a teaching schedule) no one is really telling you what to do with every minute of your time, it can be hard to choose what to do next – especially if all the tasks seem equally important.
My personal experience is similar, but also somewhat different. Continue reading Stop the “Flipping”
This is an interesting article from The Guardian on “post-truth” politics, where statistics and “experts” are frowned upon by some groups. William Davies shows how statistics in the political debate have evolved from the 17th century until today, where statistics are not regarded as an objective approach to reality anymore but as an arrogant and elitist tool to dismiss individual experiences. What comes next, however, is not the rule of emotions and subjective experience, but privatised data and data analytics that are only available to few anonymous analysts in private corporations. This allows populist politicians to buy valuable insight without any accountability, exactly what Trump and Cambridge Analytica did. The article makes a point how this is troublesome for liberal, representative democracies.
Nathan Silver’s FiveThirtyEight has had an excellent coverage of the US Presidential Elections with some great analytical pieces and very interesting insights in their models. Each and every poll predicted Hillary Clinton to win the election and FiveThirtyEight was no exception to that. Consequently, there was a lot of discussion on pollsters, their methods and how they – again after “Brexit” – failed to predict the outcome of the election. There are many parallels between the elections in the US and the Brexit-vote in the UK. At least for the US, however, the predictions weren’t that far off. And FiveThirtyEight in particular, gave Trump better chances than anyone else:
For most of the presidential campaign, FiveThirtyEight’s forecast gave Trump much better odds than other polling-based models. Our final forecast, issued early Tuesday evening, had Trump with a 29 percent chance of winning the Electoral College. By comparison, other models tracked by The New York Times put Trump’s odds at: 15 percent, 8 percent, 2 percent and less than 1 percent. And betting markets put Trump’s chances at just 18 percent at midnight on Tuesday, when Dixville Notch, New Hampshire, cast its votes.
Continue reading Predictions for Presidential Elections Weren’t That Bad
Michael Inzlicht has posted an article on his blog about how he lost faith in psychological science after reading the now infamous paper on “false-positive psychology” . Continue reading Michael Inzlicht on loosing faith in science
Already in September last year, Der Spiegel published an interview with Peter Wilmshurst, a British medical doctor and whistleblower who made fraudulent practices in medical research public:
In the course of the 66-year-old’s career, he conducted studies for pharmaceutical and medical devices companies, and unlike many of his colleagues, never hesitated to publish negative results. He’s been the subject of multiple cases of legal action and risked bankruptcy and his reputation to expose misconduct in the pharmaceutical industry.
A very interesting article that’s worth reading. Fact is, that companies who have a strong economic interest in the scientific process will have an impact on the quality of the research. It is, again and again, horrible to learn how far companies try to go – and often successfully do. While medical companies has always been an obvious target (and perpetrator), the problem runs deeper than the narrative of “Big Pharma”. Continue reading Fraud in Medical Research
While sitting in one of my three offices, dreaming of beautiful, exotic and serene places is just natural. Zach Both does not dream about these places, he just goes there. But he is not a travel-a-my-life type of guy, but a film maker and designer who happens to life mobile: He customized a van to have a bed and a kitchen to live where likes to while still doing his day-to-day business (more or less):
Zach Both is a young filmmaker who in a past life worked as a designer and art director. His passion for telling unique and unusual stories through filmmaking has lead him to travel the country in a van that doubles as his mobile production company.
Thankfully, he made a website explaining how he re-worked the van. He also posted a lot of pictures of the process and the result.
I really like his project and would love to make something similar for holiday travels. But after reading all the “vanual”, I might need to learn how to do stuff first. Being all thumbs does not really make this process much easier, I guess.
Having only started my PhD studies a few months ago, I am still eager and highly motivated to finish what I have just started. However, first doubts on the topic and the quality of my work already came (and went again, luckily), so I could relate to this post on the Valley of Shit:
The Valley of Shit is that period of your PhD, however brief, when you lose perspective and therefore confidence and belief in yourself. There are a few signs you are entering into the Valley of Shit. You can start to think your whole project is misconceived or that you do not have the ability to do it justice. Or you might seriously question if what you have done is good enough and start feeling like everything you have discovered is obvious, boring and unimportant. As you walk deeper into the Valley of Shit it becomes more and more difficult to work and you start seriously entertaining thoughts of quitting.
A great post, that I enjoyed reading. I will bookmark it to read it again whenever I find myself in such Valley of Shit.
A new case of scientific hoax, that happened six years ago, is currently circulating:
Six years ago I submitted a paper for a panel, “On the Absence of Absences” that was to be part of an academic conference later that year—in August 2010. Then, and now, I had no idea what the phrase “absence of absences” meant. The description provided by the panel organizers, printed below, did not help. The summary, or abstract of the proposed paper—was pure gibberish, as you can see below. I tried, as best I could within the limits of my own vocabulary, to write something that had many big words but which made no sense whatsoever. I not only wanted to see if I could fool the panel organizers and get my paper accepted, I also wanted to pull the curtain on the absurd pretentions of some segments of academic life. To my astonishment, the two panel organizers—both American sociologists—accepted my proposal and invited me to join them at the annual international conference of the Society for Social Studies of Science to be held that year in Tokyo.
Continue reading Scientific Hoaxes and Bad Academic Writing
This thread on StackExchange is circling around my Twitter timeline today and I couldn’t resist sharing it here:
Suppose we have data set (X_i, Y_i) with n points. We want to perform a linear regression, but first we sort the X_i values and the Y_i values independently of each other, forming data set(X_i, Y_j). Is there any meaningful interpretation of the regression on the new data set? Does this have a name?
I don’t want to blame the author of the question. It just offers plain ignorance of basic statistical concepts. On first sight this might be a beginner’s misunderstanding, but this totally kills it:
But my manager says he gets “better regressions most of the time” when he does this […]. I have a feeling he is deceiving himself.
This isn’t incompetence anymore – this is deliberate torture of statistics.