A recent Science-paper (.pdf) used a total sample size of N=40 to arrive at the conclusion that implicit racial and gender stereotypes can be reduced while napping. N=40 is a small sample for a between-subject experiment. One needs N=92 to reliably detect that men are heavier than women (SSRN). The study, however, was within-subject, for instance, its dependent…
[38] A Better Explanation Of The Endowment Effect
It's a famous study. Give a mug to a random subset of a group of people. Then ask those who got the mug (the sellers) to tell you the lowest price they'd sell the mug for, and ask those who didn't get the mug (the buyers) to tell you the highest price they'd pay for…
[37] Power Posing: Reassessing The Evidence Behind The Most Popular TED Talk
A recent paper in Psych Science (.pdf) reports a failure to replicate the study that inspired a TED Talk that has been seen 25 million times. [1] The talk invited viewers to do better in life by assuming high-power poses, just like Wonder Woman's below, but the replication found that power-posing was inconsequential. If an…
[36] How to Study Discrimination (or Anything) With Names; If You Must
Consider these paraphrased famous findings: "Because his name resembles 'dentist,' Dennis became one" (JPSP, .pdf) "Because the applicant was black (named Jamal instead of Greg) he was not interviewed" (AER, .pdf) "Because the applicant was female (named Jennifer instead of John), she got a lower offer" (PNAS, .pdf) Everything that matters (income, age, location, religion) correlates with…
[35] The Default Bayesian Test is Prejudiced Against Small Effects
When considering any statistical tool I think it is useful to answer the following two practical questions: 1. "Does it give reasonable answers in realistic circumstances?" 2. "Does it answer a question I am interested in?" In this post I explain why, for me, when it comes to the default Bayesian test that's starting to…
[34] My Links Will Outlive You
If you are like me, from time to time your papers include links to online references. Because the internet changes so often, by the time readers follow those links, who knows if the cited content will still be there. This blogpost shares a simple way to ensure your links live "forever." I got the idea…
[33] "The" Effect Size Does Not Exist
Consider the robust phenomenon of anchoring, where people's numerical estimates are biased towards arbitrary starting points. What does it mean to say "the" effect size of anchoring? It surely depends on moderators like domain of the estimate, expertise, and perceived informativeness of the anchor. Alright, how about "the average" effect-size of anchoring? That's simple enough….
[32] Spotify Has Trouble With A Marketing Research Exam
This is really just a post-script to Colada [2], where I described a final exam question I gave in my MBA marketing research class. Students got a year's worth of iTunes listening data for one person –me– and were asked: "What songs would this person put on his end-of-year Top 40?" I compared that list…
[31] Women are taller than men: Misusing Occam's Razor to lobotomize discussions of alternative explanations
Most scientific studies document a pattern for which the authors provide an explanation. The job of readers and reviewers is to examine whether that pattern is better explained by alternative explanations. When alternative explanations are offered, it is common for authors to acknowledge that although, yes, each study has potential confounds, no single alternative explanation…
[30] Trim-and-Fill is Full of It (bias)
Statistically significant findings are much more likely to be published than non-significant ones (no citation necessary). Because overestimated effects are more likely to be statistically significant than are underestimated effects, this means that most published effects are overestimates. Effects are smaller – often much smaller – than the published record suggests. For meta-analysts the gold…