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1:12 AM
For the number one spot... "I'm reading an obscure article (which I won't provide) and the author claims P is true. But I think not P. How can P be true when I also assert a factoid from my very narrow sub-field?"
3
 
 
4 hours later…
5:25 AM
@GeneralAbrial: I don't know... @Scortchi's #2 is pretty good. Reading an obscure article entails some effort plus questioning the article shows a minimal understanding of things. Blunt : "How to analyse this?" probably would score higher...
 
 
3 hours later…
8:49 AM
@Scortchi "rough on new users" - I read Workplace.SE. Compared to them, we are bunnies and fluffy kittens!
(And I fully support a meta thread on this. With one answer per list entry here, let people vote the best to the top. And with explanations why something is bad. Then we can actually point to that list when voting to close.)
 
 
7 hours later…
3:36 PM
I love all these contributions to the Top Ten list. If you want to keep ranking them, I invite you to use decimal numbering, such as 3.5 (midway between third and fourth), etc.
 
 
6 hours later…
9:42 PM
Was I being unreasonable here?
0
Q: How to generate heteroskedastic data for linear regression analysis given Y

HelmI have at m different points on a surface representing an organ n measures of a organ property for n subjects (such as wall thickness). These values have been stored in a matrix Y with m columns and n rows. The measures at different points are highly correlated - the correlation coefficient betw...

 
 
2 hours later…
11:23 PM
@Kodiologist Interesting case. I would have had the same intuition as you, but not the confidence to express it so strongly.
It's very mysterious to me what would make fitting n unrelated regressions a "major strength of the method", maybe that's a place to ask the poster to elaborate.
It also seems to me that the poster probably does have an XY problem, but I can't be sure.
I would probably recommend structuring the data as you do, and using a multi-level model of some kind. Seems like you know a bit more than me though.
 

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