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39 Beiträge28 Beteiligte3 Beiträge heute

#statstab #307 The C-word, the P-word, and realism in epidemiology

Thoughts: A comment on #306. Causal inference in observational research is a confusing matter. Read both.

#causalinference #observational #research #commentary

link.springer.com/article/10.1

SpringerLinkThe C-word, the P-word, and realism in epidemiology - SyntheseThis paper considers an important recent (May 2018) contribution by Miguel Hernán to the ongoing debate about causal inference in epidemiology. Hernán rejects the idea that there is an in-principle epistemic distinction between the results of randomized controlled trials and observational studies: both produce associations which we may be more or less confident interpreting as causal. However, Hernán maintains that trials have a semantic advantage. Observational studies that seek to estimate causal effect risk issuing meaningless statements instead. The POA proposes a solution to this problem: improved restrictions on the meaningful use of causal language, in particular “causal effect”. This paper argues that new restrictions in fact fail their own standards of meaningfulness. The paper portrays the desire for a restrictive definition of causal language as positivistic, and argues that contemporary epidemiology should be more realistic in its approach to causation. In a realist context, restrictions on meaningfulness based on precision of definition are neither helpful nor necessary. Hernán’s favoured approach to causal language is saved from meaninglessness, along with the approaches he rejects.

Schöner Kommentar bei #Commentary heute:
„Bernie and AOC aren’t the next big thing. They became an oldies act the moment Donald Trump was reelected, like a glam-metal band stranded in the wake of Nirvana’s breakthrough album.“

"Peer review is the worst method of safeguarding scientific integrity, except for all those other methods that have been tried from time to time." As Churchill might have said if he'd been a scientist rather than a politician.

From a conversation with a friend: theconversation.com/peer-revie

There are a lot of flaws in #peerreview as it's generally done now, and people working to improve it. But what's the alternative to the concept itself? We know what general public #commentary on #science looks like, and politicians shoehorning science into their #ideologies, and science for #profit without checks on validity ... they're all awful.

None of them can be completely avoided either, any more than the potent combination of authoritarianism and stupidity which is always trying to infect #democratic forms of #government. (Just to choose a random example.) And in fact there *should* be input into science from outside the field, because it doesn't exist in a vacuum any more than defense or education or business or religion or any other large-scale area of human endeavour.

But if there's a better way to keep science more or less on track, I'll be damned if I know what it is. The only people qualified to judge the work of scientists—not the big-picture priorities, and not the utility of the results, but the nitty-gritty of the work itself—are other people knowledgeable in the same line of work, and I don't see that changing. Same as any other job, really.

Like I said above, there are proposals for addressing peer review's flaws, and I'll be happy to expound on that if anyone likes.

The ConversationPeer review is meant to prevent scientific misconduct. But it has its own problemsThe peer review process is central to science – but it can be easily manipulated. Improving it is vital to uphold research integrity.