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Kristina Olson Profile picture
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Apr 29 • 3 tweets • 1 min read
I'm starting to prep a grad class on research ethics in psych research. I'm looking for great examples of gray areas -- not clear cut wrong/right. Do you have favorites for active discussion? Any cool examples presented in media (podcasts, tv shows, print media)?
Also, we are thinking about "research ethics" more broadly than some people do -- we are including sexual harassment, bullying, authorship, psych scientists' role in media, govt, and industry, etc.
#PsychTwitter for the win on this one! I can't believe how many amazing suggestions are rolling in. I'd love more that are relevant to #CogNeuro & computational approaches as that's a big contingent of students in my class!

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Kristina Olson Profile picture
Nov 18, 2019
Today's an exciting day for my lab as a paper came out for which we collected data for 4 years and then spent 3 years writing up the results. With contributions from nearly everyone in my lab at the time--this one gets a special thread. pnas.org/content/early/…
The main findings: overall, the 300+ trans kids don't differ from 500+ cis kids (including sibs of trans kids) on measures of gender development, in terms of means + distributions.
We find no significant associations between how long it's been since someone socially transitioned and the strength of their gender identity of degree of gender-typed preferences (e.g., for toys, playmates, etc).
Read 11 tweets
Kristina Olson Profile picture
Jan 15, 2019
One other point on this paper. Something I still struggle with: What happens when the stats that are best for a paper are stats that 95% of the field and esp readers won’t understand? We tried out best to explain them, but if we’re honest, even all of us don’t fully understand.
Getting an editor + reviewers who were savvy was key. But it is unrealistic that everyone will understand increasingly complex analyses & it’s unlikely that non-scientists will. What do we do? Is it ok that so many people do not understand many details of the results section?
Simple stats (t-tests, regressions) told the same story as the fancy Bayesian analyses (though the latter let us support the null). Part of me wondered about putting both the wrong but simple ones and the right but hard ones so more people understood.
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