Timeline for When is it important for a practitioner to understand CIs?
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
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| Apr 16, 2024 at 8:08 | comment | added | Dikran Marsupial | @ChristianHennig Completely agree with the last sentence! My own view is that we should try to use the tools that answer our questions most directly - if we need a prior to do so, then we should do that (and be aware/discuss potential issues). It is not as if frequentist statistics is completely free of prior knowledge/subjectivity - it is how we ought to decide on appropriate significance levels etc. I think the burden should be more on the writer of the paper than the reader as that would be a more efficient approach. | |
| Apr 15, 2024 at 22:30 | comment | added | Christian Hennig | @DikranMarsupial In my experience practitioners would be happy to have a probability statement for the true parameter, and they would be happy to get this without having to provide a prior. Also they don't want to know that the true parameter is defined within a model which is "wrong", as all models are, so the "true parameter" doesn't really exist. Sometimes we better tell practitioners that we can't provide what they want than pretending to do so. | |
| Apr 15, 2024 at 17:51 | comment | added | Dikran Marsupial | I don't see it as that high a standard, as I said elsewhere CIs are a fairly basic concept that ought to be basic competence for practitioners, but I do agree that is not how things actually are. Kudos to the practitioner involved in this case for not being comfortable with their understanding and seeking advice. That is far better than being overly confident in, shall we say, "less than perfect" understanding. The real problem is that CIs are only a rather indirect answer to the question the practitioner really wants answered. | |
| Apr 15, 2024 at 17:40 | comment | added | Demetri Pananos | @DikranMarsupial I think you are holding a very high bar here for statistics and statistical practice in medicine -- which I anticipate is well meaning, but unfortunately unfeasible in most scenarios. There is a happy medium where good research can be done without having perfect understanding of exactly what the estimators are. | |
| Apr 15, 2024 at 11:01 | comment | added | Dikran Marsupial | The physician should collaborate with a medical statistician to help ensure the statistics are correct and correctly presented. Confidence intervals and credible intervals can often be safely confused because there is a prior for which they are numerically the same. However you need to know the difference for the cases where confusing them is not benign, especially for safety critical applications , like medicine. | |
| Apr 14, 2024 at 18:00 | history | answered | Demetri Pananos | CC BY-SA 4.0 |