Synopsis of Social media discussions
The overall tone reflects mild enthusiasm and curiosity about the article’s themes, with examples like trying new software tools and questioning why experts might neglect the concept of prediction intervals, using phrases such as 'use R to do the same thing' and 'why some Harvard PhDs don't use PIs.' The language suggests an early-stage interest rather than a highly impactful or deeply engaged conversation.
Agreement
Moderate agreementThe first post hints at an endorsement or curiosity about the usefulness of prediction intervals, while the second suggests ongoing questions in the field, indicating some support with an interest in further understanding.
Interest
Moderate level of interestBoth posts express personal engagement with the topic—one through trying out tools and the other through questioning practitioners—demonstrating moderate curiosity rather than strong passion.
Engagement
Neutral engagementThe discussion is relatively surface-level, mentioning tools like R and raising questions without deep technical analysis or extensive debate.
Impact
Neutral impactThese posts seem to reflect a general awareness rather than emphasizing the publication’s transformative potential or widespread influence.
Social Mentions
YouTube
2 Videos
20 Posts
2 Posts
News
5 Articles
Metrics
Video Views
252
Total Likes
23
Extended Reach
2,548
Social Features
29
Timeline: Posts about article
Top Social Media Posts
Mihai Dinu
Just came across my first youtube clip.
Not a plug. Use R to do the same thing (actually easier if you're in front of computer).
@EpiEllie you still haven't answered my question regarding why some Harvard PhDs don't use PIs. Maybe this will help them!
https://t.co/Wy0cqoU1Bt
view full post
Mihai Dinu
You don't have to take my word for it
view full post
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Just came across my first youtube clip. Not a plug. Use R to do the same thing (actually easier if you're in front of computer). @EpiEllie you still haven't answered my question regarding why some Harvard PhDs don't use PIs. Maybe this will help them! https://t.co/Wy0cqoU1Bt
view full postNovember 3, 2024
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Mihai Dinu
@mihaidinu88 (Twitter)You don't have to take my word for it
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Abstract Synopsis
- The article emphasizes the importance of routinely including prediction intervals in meta-analyses, as they provide a clearer understanding of the range of true effects across studies and help interpret the uncertainty about intervention effectiveness.
- Research findings from Cochrane reviews show that in many cases, the prediction intervals suggest the intervention's effect could be null or even opposite to the overall estimate, highlighting the variability across different settings.
- Prediction intervals can also be used to estimate the likelihood that a new trial will yield a negative result and to improve the planning and power calculations for future studies, making them a valuable tool for clinical decision-making.
Mihai Dinu
@mihaidinu88 (Twitter)