Top Tweets for #StatsWithCoreIM
1/ Welcome back to #StatswithCoreIM !
A rapid antigen test for COVID-19 has a 98% sens. and 99% spec. It was studied in ICU pts with PCR-confirmed COVID-19 and PCR (-) adults in the community (controls). ALL pts received both rapid &PCR tests.
Which type of bias is present?
1/ How can you ⬇️ bias in observational data? #StatswithCoreIM
Propensity score matching (PSM)! 🧵
Analogy:
Randomization🤝RCT
Propensity score matching🤝Observational study
9/ That’s all for #StatswithCoreIM. Thanks for learning some #biostatistics with us this Wednesday and big shout-out to the author with this byte Dr. Robert Wharton and graphics by @ivannatang
For more #noninferiority trials byte: https://t.co/Dwc1EamIZE
1/ Let’s dive into #noninferiority trials for this edition of #StatswithCoreIM
But first, take a look at this figure for what superiority trials aim to assess: What’s better?
1/ What are 3 Qs you can ask yourself when looking at non-inferiority trials?
Q1) Was the trial planned i.e. pre-specified as comparing an intervention which is non-inferior to control?
WHY?
Bc changing the analysis *afterwards* introduces bias #StatswithCoreIM
@AmmariDr Hi, Your thread is ready to read. 1/ Let’s dive into #noninferiority trials for this edition of #StatswithCoreIM But first, take a l https://t.co/dNS8RRympx
Have a good day!
@imran_rob Hi, Your thread is ready to read. 1/ Let’s dive into #noninferiority trials for this edition of #StatswithCoreIM But first, take a l https://t.co/dNS8RRympx
Have a good day!
1/ Let’s dive into #noninferiority trials for this edition of #StatswithCoreIM
But first, take a look at this figure for what superiority trials aim to assess: What’s better?
@imran_rob Hi, Your thread is ready to read. 1/ Welcome back to #StatswithCoreIM ! What would you tell this patient who inquires about lab canc https://t.co/EILHDdbAkJ
Have a good day!
1/ Welcome back to #StatswithCoreIM !
What would you tell this patient who inquires about lab cancer #screening test to help him “live longer”?
What types of bias can occur in determining whether a cancer screening test reduces mortality?
1/ Hey #medtwitter, what do you know about diagnostic odds ratios and how they are used?
It’s time for another round of #statswithCoreIM!
Let’s start by considering dichotomous test characteristics:
Thankful to this #StatswithCoreIM for helping me cement better #LikelihoodRatio and it’s application to test results 🙏🏾
3/ As difficult as the concept can be to grasp, our understanding of it is crucial. Without it, we run the risk of misinterpreting the meaning of test results!
5/ To see the full post on our website, as well as other #StatsWithCoreIM post, check out our website! https://t.co/cFoA7IRYtI
1/ Don’t let likelihood ratios do a number on you! Today, we will try to demystify them in another installment of #StatsWithCoreIM
If you have a positive test result on a test that is 90% sensitive and 90% specific, how does it impact your chance of truly having the disease?
6/7 Without understanding your patient’s pre-test probability, sensitivity and specificity alone are simply insufficient.
And that concludes our #StatsWithCoreIM post for this week. Hope you learned something!
5/7 This is the crux of the issue, and where we often get ourselves into trouble. #StatsWithCoreIM
4/7 Ditto here for specificity, though now the people are represented in teal and they’re as healthy - whatever disease you’re testing for here, they ain’t got it. #StatsWithCoreIM
3/7 For the visual learners out there, we’ve tried to explain sensitivity using the picture below. Take note: every individual represented in🍊 is 🤒- they already have the disease. #StatsWithCoreIM
2/7 We start with definitions. Boring? No! Understanding these terms is crucial to helping us judiciously order and interpret tests. #StatsWithCoreIM
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