At the very least, the pattern does not seem to be as clear as implied from some media reports. (Even a glance at the paper by Stone, Schwartz, Broderick, and Deaton, which is the source of the top graph above, reveals a bunch of graphs, only some of which are U-shaped.)
But what I found the most interesting is that the sub-graphs are on different elements of "well being" (stress, worry,enjoyment happiness, sadness, anger). I wonder if the higher well being among older adults is, in some sense, very different than that of younger adults. Less stress and worry may contribute to increased (overall well being) but it might be a very different positive state than one created by the limitless potential of youth.
So I suppose I wonder if representing a complex vector (as well being has many factors that contribute to it) as a scalar (singl question) might not be eliminating the most useful sources of variability? Even if this approach is the standard in the field, it does not mean that we can't benefit from seeking a more complicated understanding of the phenomenon. I think that Andrew Gelman is on the right track in trying to really understand this complicated (and interesting) relation.
"So I suppose I wonder if representing a complex vector (as well being has many factors that contribute to it) as a scalar (single question) might not be eliminating the most useful sources of variability?"ReplyDelete
This is a big subject and it demands a post of its own but the answer is an emphatic 'yes.' This is one of those ideas that is difficult to see not because it's subtle but because it's obvious: whenever you represent a vector with a scalar you lose information and you run the risk of not seeing something that's there or seeing something that's not.