On the About page I wrote, that I blog about things I come across while researching for my PhD. So, you may very well ask what this PhD is supposed to be about. For the interested reader — researchers and the uninitiated alike —, here is some overview on my current plans and research focus.
A lot of debate (and part of my thesis) revolve around replicability and the proper use of inferential methods. The American Statistical Association has now published a statement on the use and the interpretation of p-Values (freely available, yay). It includes six principles and how to handle p-Values. None of them are new in a theoretical sense. It is more a symbolic act to remind scientists to properly use and interpret p-values.
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.
Over at the Non Significance blog, the author describes the case of a paper that has some strange descriptive statistics:
What surprised me were the tiny standard deviations for some of the Variable 1 and 2, especially in combination with the range given.
In the blog post, the author outlines his approach to make sense from the descriptive values. It seems to be likely that the reported Standard Deviations (SD) are actually Standard Errors of the Mean (SEM). I’d like to add to this blog post one argument based on calculus and one argument based on simple simulations to show that SEM’s are indeed much more likely than SD’s.1 Continue reading “Mixing up Standard Errors and Standard Deviations”
Bad enough, that we have to read und hear current failures of thought by right wing populists (article in German only) and many relativizations (comments in German only). It seems like 70 years of History class did not help to stop utter racism in public debate.
What, however, sparked my interest was the question what correlations with birth rates there are. My intuitive expectation was, that higher life expectancy is linked to lower birth rates, what might also be explained from an evolutionary perspective.
Now, I’m neither an anthropologist nor do I know the current state of research and I can only use openly available statistics. Luckily, the World Bank has a large database with various indicators for all countries and regions of the world.
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.
After I found out about the panel discussion on Good Scientific Practice at the University of Cologne via Twitter, I joined yesterday to watch the discussion as it was closely related to my thesis’ topic.
The panel was filled with five professors and one junior professors from different faculties1, whose positions were related to “good vs bad science” in some way.
The German Society of Psychology (DGPs) today announced that the court of honor has put an end to its investigation on Jens Förster after they mutually agreed to the retraction of two papers in the Journal of Experimental Psychology: General:1
By this [agreement] the proceedings against Prof. Dr. Jens Förster at the court of honor at the German Society of Psychology will be concluded. Prof. Förster is obliged to act upon the publishers of the Journal of Experimental Psychology to pursue a retraction of the following to publications:
Förster, J. (2009). Relations between perceptual and conceptual scope: How global versus local processing fits a focus on similarity versus dissimilarity. Journal of Experimental Psychology: General, 138(1), 88-111. http://dx.doi.org/10.1037/a0014484
Förster, J. (2011). Local and global cross-modal influences between vision and hearing, tasting, smelling, or touching. Journal of Experimental Psychology: General, 140(3), 364-389. dx.doi.org/10.1037/a0023175
This settlement is neither a confession of guilt by Prof. Förster nor an imputation of blame by the court of honor.
Past analyses and reports have hinted at a possible scientific misconduct, but he always denied those claims. However, this settlement is rather strange to me: either there is sufficient evidence of fake data or very questionable practices or there is none. In the first case, an investigation should formally be started to identify any publication that might be based on those data. And in the latter case a retraction seems unreasonable – what reason should a retraction have in that case? Especially when both parties are so eager to underline that no confession of guilt or blame is made.
Seems like I’m not the only one wondering about this course of events:
Er… Weird https://t.co/YN0XrZVb7v
— Andrew & Sabrina (@PsychScientists) November 12, 2015
Odd deal. https://t.co/6ycssIO5tT
— JP de Ruiter (@JPdeRuiter) November 12, 2015
I’m pretty sure that this is not the end of the discussion and that there will be other investigations.
Inspired by a recently published article in the ZEIT (in German only), I did some further reads on the topic of mosaicism. The bottom line: contrary to common belief and what is taught in text books (and University courses), the human body does not consist of cells with a single, personal genome, but instead each cell or cell-cluster has it’s own personal genome. A phenomenon that is also called “mosaicism”.
Until recently we needed a bunch of cells that were used to sequence our DNA, but today we are able to look on our genes on a single-cell basis. Findings now reveal a new theory on how our cells and tissue has evolved and allows for new theories on somatic and psychiatric illnesses.
From a review by Biesecker and Spinner (2013)1:
It has long been known that cancer is a mosaic genetic disorder, but mosaicism is now apparent in a diverse range of other clinical disorders, as indicated by their tissue distributions and inheritance patterns. Recent technical advances have uncovered the causative mosaic variant underlying many of these conditions and have provided insight into the pervasiveness of mosaicism in normal individuals.
This not only changes how we should think about the genetic basis of diseases but also about the genetic basis for personality and “normal” human behavior.
From this findings new theories of genetics and the genetic causes of human differences and diseases will emerge. We are not a single piece of cells with a pre-determined DNA, but a bunch of cells with different and still ongoing mutations in a DNA, that begun with only a single cell. This is fascinating and shows the ever-evolving nature of science and that we have by no means already “discovered everything that can be discovered”.
- Zimmer, C. (2013). “The Dark Matter of Psychiatric Genetics”, Phenomena, A Science Salon (National Geographic). http://phenomena.nationalgeographic.com/2013/12/20/the-dark-matter-of-psychiatric-genetics/
- Lupski, J. R. (2013). Genome Mosaicism–One Human, Multiple Genomes. Science, 341(6144), 358–359. http://doi.org/10.1126/science.1239503