3 ms·
we tried using 0.10 mL, it didn't work we tried using 0.11 mL, it didn't work we tried using 0.13 mL, it didn't work we tried using 0.15 mL, it didn
by harry8 5y ago
we tried using 0.10 mL, it didn't work
we tried using 0.11 mL, it didn't work
we tried using 0.13 mL, it didn't work
we tried using 0.15 mL, it didn't work
we tried using 0.17 mL, it didn't work
we tried using 0.16 mL, it didn't work
we tried using 0.18 mL, it didn't work
we tried using 0.20 mL, it didn't work
we tried using 0.14 mL, it didn't work
we tried using 0.12 mL, it worked so we published
Do you want to know the ones that "didn't work" existed? Or are you happy with just the one that "worked" being written up in isolation?
- hprotagonist 5y agoi don’t want to know about each test that didn’t work as a separate publication, that’s for sure!
- carlmr 5y agoThat's true, we would need a way to collect this data so it's easily seen as part of a whole. E.g. if you search for eggs and cholesterol you should find all studies with their summarized results on whether eggs are ok or not for your cholesterol, grouped by researcher, so if somebody does 200 studies to find the one positive it's instantly visible.
- PeterisP 5y agoYou would read a meta-study that summarizes those tests - especially because they might potentially made by different labs, and the fact that one of them worked might be actual a real effect caused by some other difference in the experiment.
- harry8 5y agoEspecially for small effect size and suppressing what didn't work, this is one obvious way of many to perform p-hacking for publication acceptance. https://en.wikipedia.org/wiki/Replication_crisis https://en.wikipedia.org/wiki/Replication_crisis