Yeah but I'm still curious what people are doing with them re causality that they are not doing (or doing less) with cross sectional data :) :)
Ok, but that temporal footprint also exists for the cross-sectional case where people try for causality with observational data, no? Whether or not we observe the earlier times, lots occurred that might confound any apparent causal relation. Just curious why growth curves generate this concern...
I thought growth curves were fairly innocuous... you just want to describe change over some period, and in the multivariate case, correlations in slope across constructs. There's potentially 3 billion factors leading to the change, but we don't care. What is it that gets confounded?
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So long as we stay at the point of civilisation where yield is largely decoupled from population change :)
Hah true, wasn't even thinking of that angle, just the general badness of getting to the bump in the first place. Maybe mostly a historical issue by now though, I guess bulk of population is already near or post bump...
I like human development, equality etc, but :) the environment relationship seems rather non-monotonic to me, curious if there's a solid argument for reducing inequality being a general positive for the environment and not just a progressive feel-good bundle package?
ctsem 3.10.1 is on CRAN, mostly fixing a bug introduced last update when outcome variables are both continuous and binary, and including a function for improved visualisation of moderation effects. cran.r-project.org/web/packages...#psychology#rstats
As an Aussie, living in Amsterdam for a bit changed me forever... can't go back to the sprawl.