Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/eb7cOAez5Z
References: - Gelman, A. and Hennig, C. (2017), Beyond subjective and objective in statistics. J. R. Stat. Soc. A, 180: 967-1033. https://t.co/MgSvKMXPyB - Weinberger, D. (2009) Transparency is the new objectivity. Everything is miscellaneous blog, July…
what a wonderful opportunity for inquiry on why metascience studies reported with narrative are so important cc @stuartbuck1 @notanastronomer @DefenderOfBasic we have obv known "fMRI can be kinda useless" but we have not communicated "where, exactly, d…
this isn't new, but yeah fMRI data has always been problematic see: https://t.co/KvdiKYPdFL & https://t.co/yOG5t1I8T9 for decent overviews on the limitations and considerations re: fMRI https://t.co/ezN0FeIVtW
@ActAppalledxx @lordesbbqribs Congrats. I’m aware of the paper too. Has your Bachelor’s degree helped you maintain enough interest in the field for you to be aware that this paper inspired an additional paper, specifically because of the unreliability of …
link to the Nature paper: https://t.co/fTViQAaFUM
RT @rotembot: It was a pleasure talking with @fMRI_today about analytical variability #narps https://t.co/mQ9j8ZHanG, promoting open & repr…
RT @rotembot: It was a pleasure talking with @fMRI_today about analytical variability #narps https://t.co/mQ9j8ZHanG, promoting open & repr…
This was a wonderful conversation not only about the implications of the seminal paper comparing the results of many different labs analyzing the same data set, but much more!
RT @rotembot: It was a pleasure talking with @fMRI_today about analytical variability #narps https://t.co/mQ9j8ZHanG, promoting open & repr…
RT @rotembot: It was a pleasure talking with @fMRI_today about analytical variability #narps https://t.co/mQ9j8ZHanG, promoting open & repr…
RT @rotembot: It was a pleasure talking with @fMRI_today about analytical variability #narps https://t.co/mQ9j8ZHanG, promoting open & repr…
RT @rotembot: It was a pleasure talking with @fMRI_today about analytical variability #narps https://t.co/mQ9j8ZHanG, promoting open & repr…
It was a pleasure talking with @fMRI_today about analytical variability #narps https://t.co/mQ9j8ZHanG, promoting open & reproducible science (https://t.co/o0XcwCRyPG; https://t.co/jXqMOxpmxx; https://t.co/nOrjh2GXqn), placebo effects https://t.co/P…
@DrGoblin3 @Lageraemia @robertrea @BibiLynch One swallow does not make a summer, one battle does not win a war! Chk out "Variability in the analysis of a single neuroimaging dataset by many teams" https://t.co/25ARKmC0WE via @tschonberg et al Are we su…
@Aella_Girl You are not the only one (maybe you've seen this one already): https://t.co/5gbJdZzbbp
Another example of what has been reported in #fMRI (https://t.co/xYUHOJv5Fd). Is multiverse analysis the way to go or are there other ways to take this uncertainty into account in the scientific process?
@AnilOza16 @JkayFlake @HannahSFraser @TimParker88 @Elliot_Gould_ @Nicole_C_Nelson @BrianNosek At least the lack of reproducibility replicates 😆 https://t.co/gtGoFYHOh9
This isn't just an issue in one discipline tho. And there are many reasons why it occurs. Some of it is due to QRPs, some of it due to analytic flexibility plus the reliability of the measures used (e.g., https://t.co/LgMzL305oA, https://t.co/6WKw4dcAM4…
@szorowi1 Same here Not sure if you’ve seen but relevant. Some of the variability in analysis and preprocessing here is due to default settings between software https://t.co/XDKCo1QlPE
Had an amazing time at our inaugural @ReproducibiliT meeting - looking forward to more discussions with all of the amazing scientists at @UCSBpsych! Note to self - keep eyes open in future pictures
RT @avamadesousa: A great turnout for the inaugural @ReproducibiliT meeting at @UCSBpsych discussing a spicy fMRI paper*! 🍵🔍🧠 Excited for…
I should definitely smile more next time haha, like @madhurik951
Thank you, @avamadesousa, @madhurik951, and Amber Chen! So psyched we have our own @ReproducibiliT at @UCSBpsych now!
A great turnout for the inaugural @ReproducibiliT meeting at @UCSBpsych discussing a spicy fMRI paper*! 🍵🔍🧠 Excited for more fun discussions and workshops to come 😃 *https://t.co/0g1Wd8iYoS https://t.co/EAy1S9hBq1
@micahgallen We know that there is great model dependency in the multiverse of madness. But that's true everywhere. @rotembot https://t.co/qVCKIO5BD8
RT @sNeuroble: @neurograce There are a number of papers that say there are major challenges that hinder progress, but I think most (incl us…
@neurograce There are a number of papers that say there are major challenges that hinder progress, but I think most (incl us) don’t go so far as to say the field is not progressing altogether. E.g., questioning common neuro designs/methods https://t.co/5…
Recall yesterday's event... 🍕🧠 #SanoScience #neuropizza @psychologyUJ
RT @brain_more: Today's Neuropizza @SanoScience we talked about harmonizing multisite neuroimaging and @lola_dachshund almost got the pizz…
Today's Neuropizza @SanoScience we talked about harmonizing multisite neuroimaging and @lola_dachshund almost got the pizza. https://t.co/gBOPvo6xre #neuroscience #neuroimaging #journalclub https://t.co/0Q0GkH8EHI
And the variance is gigantic too, assuming that scientists will all interpret the scan data the same way. BUT they don't, 70 teams examined the same scan data and came to vastly different conclusions https://t.co/vpfJTL9ySQ
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
Variability in the analysis of a single neuroimaging dataset by many teams | Nature https://t.co/ZBbr1nYHL9
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
RT @pash22: Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @Alb…
Variability in the analysis of a single neuroimaging dataset by many teams https://t.co/25ARKmCyMc via @russpoldrack et al @AlbertoEspay @MadhavThambiset @MemoryDoc https://t.co/fc5uFv8YCR
RT @ItaiYanai: Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in differ…
Looking is not the same as seeing: a single dataset can lead to different conclusions, when each group analyzes it in different ways, finding often contradictory results, as this important paper shows. https://t.co/GupZOFSi1c @rotembot @ten_photos @russ…
@DrGrosman Depends on which branch of medicine. Less of a problem with clinical trials, but arguably the same with epidemiological and other observational studies, and pre-clinical studies, eg neurosciences. Concerning the latter, see https://t.co/WUu…
@GivingTools This paper in Nature might be the one: https://t.co/d69lgZZyBx
@rahsaanmax @chris_bail 1. The problem isn't limited to social science. See e.g. https://t.co/mSvA7QcOyI 2. The problem isn't due to lack of precision (in e.g. measurement), but due to the inevitably large number of choices and decisions that have to …
@AndreaLGardner Here's one with fMRI data https://t.co/qVCKIO5BD8
@wgervais Reminiscent of this... https://t.co/OzBDIwmWvy
@hsquaredfan @Sniffy2 @RCownie @evopsychgoogle That meta analysis is pretty weak support of your point though. They even state the correlation is weak, and even then still are likely inflated. Speaking of results not replicating, I'm not a fan of MRI s…
A very interesting issue https://t.co/lBFEWHicey
@thinkin_mkdeabh @Nicolas_Adenis @JeremyLewisPT These are two landmark papers of fMRI methodology. If this study was published today with the same results, n=80, demand characteristics and I would be very impressed. probably will never happen. https://…
The results of this @nature article emphasize the importance of validating and sharing complex analysis workflows and demonstrate the need for performing and reporting multiple analyses of the same data. https://t.co/wzuPsFNJjf
@JScholar Brain imaging is tricky to study... Here's another study (from a lab in TAU!) that highlighted another type of issues that can lead to findings that don't replicate: https://t.co/RXGD2st2EK It's nice to see this issue getting more attention.
Door 23 of the #AdventOfRepro calendar
RT @FinRepro: 2️⃣3️⃣🎄🎁 #AdventOfRepro Our Twitter advent calendar of #reproducibility is soon over! 😱 🤶🏼🎅🏻🧑🏿🎄 Today a contemporary classic…
RT @FinRepro: 2️⃣3️⃣🎄🎁 #AdventOfRepro Our Twitter advent calendar of #reproducibility is soon over! 😱 🤶🏼🎅🏻🧑🏿🎄 Today a contemporary classic…
RT @FinRepro: 2️⃣3️⃣🎄🎁 #AdventOfRepro Our Twitter advent calendar of #reproducibility is soon over! 😱 🤶🏼🎅🏻🧑🏿🎄 Today a contemporary classic…
RT @FinRepro: 2️⃣3️⃣🎄🎁 #AdventOfRepro Our Twitter advent calendar of #reproducibility is soon over! 😱 🤶🏼🎅🏻🧑🏿🎄 Today a contemporary classic…
2️⃣3️⃣🎄🎁 #AdventOfRepro Our Twitter advent calendar of #reproducibility is soon over! 😱 🤶🏼🎅🏻🧑🏿🎄 Today a contemporary classic by @rotembot and many others: “Variability in the analysis of a single neuroimaging dataset by many teams” https://t.c…
@edwinderaaij @PhysioMeScience Apparently, in fMRI research results are never what they are! If it wasn’t replicated it never happened and if it was replicated once, it should be replicated again. Until then, our interpretations and language we use are th…
@mnrajah @joelsnyder12 yes, the fMRI one came out last year: https://t.co/hq1qMgwfcO
CRS ReproducibiliTea today! @rotembot presents "Variability in the analysis of a single neuroimaging dataset by many teams" https://t.co/npO7FakP5i Looking forward to a great session and a great semester organised by @MartynaPlomecka! Details he…
For example of multiverse in #fMRI see: e.g., https://t.co/bSk4tExwOn
Inspired by works in diffusion (Jones et al. https://t.co/keXAqRshcY) fMRI (Botvinik-Nezer et al. https://t.co/1AkLoBxihC) and manual segmentation (Boccardi et al. https://t.co/2IORjUzbAi)
fMRIデータのMany analystsも紹介したかったのですが、中の人曰く、準備時間が追いつきませんでした。Botvinik-Nezer et al. (2020). Variability in the analysis of a single neuroimaging dataset by many teams. Nature, 582(7810), 84–88. https://t.co/sulFrwDkHV
@deaneckles In the interim, there's https://t.co/kX9F7Mwa64 that is experimental (rather than observational) but it's hard for me to parse the difficulty of the research Q, and the data sets/analyses involved are far more complicated.