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Laurie beat me to it. :)
everyone is welcome to add notes, questions, thoughts to the linked document above
Heidi, you might want to re-post the link to the agenda, for those who joined late
Here it is: https://docs.google.com/document/d/14K-4NLD2m8YgGZteJIh7YoSXyGMwAaJQcIs9Xpm-h14/edit
My own experience running “newborns" after we got kicked out of hospital due to Covid is that parents of newborns revert to the oldest possible day they can come in -- as in, we'd get a lot of 6 week olds
@laurie: Pooling across labs works OK - from a multi-level models perspective you just want random age slopes by lab as well as a fixed effect of age across labs.
(in MB1 we did a meta-analytic approach that would mean that incomparable ages across labs would be hard to deal with, but we've moved away from that analytic strategy in subsequent projects, which all use mixed models)
great point above also from Kiley Hamlin re: recruitment. we didn't see this online (there was a decent range within the 0-45 eligibility window) but in the lab it may be harder to recruit younger babies if the window is large?
+1 on this being something foundations might be interested in!
(or, maybe that's a related point to what Mike said ;)).
@kiley - this feels like it connects well with Templeton priorities.
Sorry all I didn't realize I was messaging a select group -- just noting this in particular feels like a very foundation-friendly topic
@Jonathan - note that MB2 is doing exactly what you are describing, that is doing some pre-registered analyses on trial 1 but then analyzing and modeling carryover for multiple trials.