I have seen studies about damages that social media can cause in behaviours. Smartphones are the catalyst to social media consumption as we know. This might be one of them.
Like people contantly on their phones everywhere instead of interacting with other people, for example.
Plenty has been written about how any technological innovation leads to massive societal changes no one could foresee, and no one could avoid, but only analyze in retrospect.
LMAO does the author really take themselves seriously as they type that.
This author has no understanding of statistical methods. This sort of article is the reason why people distrust science. Not because the scientific method is flawed, but rather because nonsense like this get published.
Because people who had iPhones during the AT&T exclusive period has less kids...
They think there is no other possibly explanation besides the iPhone, because they looked at similar groups on different networks and in different areas that didn't yet have coverage for iPhones?
It definitely couldn't have been due to richer people having iPhones and having less kids, or people preferring iPhones who weren't going to have kids anyway??
Why definitely not? And why definitely iPhones or Smart Phones or whatever?
At the end of the abstract they state the likely explanation of this seemingly spurious correlation: > National-survey evidence on time use and sexual behavior is consistent with the iPhone reducing in-person interactions, increasing pornography use, and reducing sexual frequency.
As a rule of thumb, if you look at something for 3 minutes and have some obvious questions, the scientists that looked at it for several years of their life in great detail might have had those same obvious questions as well.
This is patently ridiculous.
> As a rule of thumb, if you look at something for 3 minutes and have some obvious questions, the scientists that looked at it for several years of their life in great detail might have had those same obvious questions as well
This does not mean that just because they had those obvious questions that they were properly resolved. Human history has a long track record of people who knew better but chose to ignore. In science there is an incredible pressure to have positive results rather than negative ones (IE nobody would care or know about this study if the title was "we looked and iphone doesn't explain 33-52% of fertility decline"
1) A causes B
2) B causes A
3) C causes both B and A (in some order)
4) your correlation figure is bullshit (hence not counted in the 3 options, but certainly with news these days, it must be mentioned)
A famous way to illustrate where this goes wrong is to show a map which libraries that loaned out Harry Potter books, and a map of where poodles got raped. Very high correlation, and obviously an example of the 3rd option.
(obviously both were caused by population density, which leads to both library creation and poodle-related crimes. And probably non-poodle-related crimes)
That often results from p-hacking. In a world of infinite variables, if you look hard enough you are guaranteed to eventually find two completely unrelated variables that correlate with each other over a statistically significant period of time.
Let me get this straight, I believe one needs to read a paper to get it straight.
But I fully understand your knee-jerk reaction. That was my reaction when I read the title too. However, it seems to be a surprisingly well-thought analysis where all your points are answered (controlled).
If I read it more thoroughly I'll likely find flaws on the statistical methods. But it's not like the authors didn't have common sense.
"Table 1 documents that treated counties (those with >90% AT&T 3G coverage) are substantially more urban, White, Republican-leaning, and affluent than control counties. To address this imbalance, we apply the entropy-balancing reweighting of Hainmueller (2012), which solves for the entropy-minimizing set of control-county weights that equalize the treated and reweighted-control means of a specified set of covariates."
throwa356262•25m ago