I stumbled upon an article which used a Bonferroni correction to ‘control’ family-wise error rates. While this isn’t shocking by itself, I was happily surprised by how they applied it. This is what they wrote: “In order to account for multiple comparisons, statistical significance was set at a p-value of less than 0.0056 (.05/9 tests) using … Read more
Do you believe in peer-review, or would you rather get rid of this false token? Do you call out people who publish statistical errors, or do you think doing this is methodological terrorism? Do you seek to advance your personal goals, or do you above all value the pursuit of science? In other words… what is … Read more
(Note: If you haven’t done so yet, be sure to read my earlier blog post as an introduction to the 4 papers with 150+ inconsistencies) Many scientists will at some point in their academic career play a game about research ethics involving discussions of case descriptions. These cases typically start with a description of a tricky scenario, for … Read more
As scientists, what are we doing? Someone once told me that when you study education (like I do) your job is to separate that which is obvious and false, from that which is obvious and true. In other words, we can often think we know something, but with a scientific methodology we can figure out if we are justified … Read more
I originally started this blog arguing why we need to be skeptical scientists. First, we need to be skeptical of our assumptions, our way of thinking, and the studies we do. Second, we need to be skeptical of the scientific literature we read. We cannot simply read a study and take it face value, we have … Read more
UPDATE: To see how science should absolutely not been done, see our investigation of 4 papers which total over 150 errors. I am but a phd student, only just starting to crawl my way into academia. Yet even the little ones are allowed to dream big, and this is my dream of how science will be … Read more
Almost all data is hierarchical. Only multilevel design properly account for this. Don’t generalize to what you didn’t sample from.