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A New Explanation For the Plight of Winter Babies
Ant passes along a Wall Street Journal report on research that turned up a new explanation for the lifelong challenges experienced by winter babies. "Children born in the winter months already have a few strikes against them. Study after study has shown that they test poorly, don't get as far in school, earn less, are less healthy, and don't live as long as children born at other times of year. Researchers have spent years documenting the effect and trying to understand it... A key assumption of much of that research is that the backgrounds of children born in the winter are the same as the backgrounds of children born at other times of the year. ... [Economist] Mr. Hungerman was doing research on sibling behavior when he noticed that children in the same families tend to be born at the same time of year. Meanwhile, Ms. Buckles was examining the economic factors that lead to multiple births, and coming across what looked like a relationship between mothers' education levels and when children were born." Here's a chart in which the effect — small but significant — jumps out unmistakeably.
Of course the difference jumps out. The chart was deliberately designed to make the change jump out by not using 0 as the origin of the Y axis.
This is a very common technique for making a difference look a lot larger than it actually is.
The cake is a pie
There's a tendency for promiscuous, uneducated teenagers to have unprotected sex during springtime and early summer. It's always easy to say this, but, duh...
Any measurement made requires two peices of information: the measurement and the uncertainty associated with that measurement. To present data as though its known with 100% certainty is misleading and incorrect. It seems pendantic to worry about uncertainty, but when you're dealing with small effects on the order of less than one percent, if the error bars are +/-2.5%, then it's absolutely incorrect to refer to the result as "jumping out".
You could do better... if you were born in June.
If you count backward from January, that puts conception around April/May. Right around graduation. So if you suppose the poor and less educated would be getting married and starting a family instead of getting ready for college, that might explain some of it.
It would probably be just as interesting to track the birth rates correlated to surges in beer and Jagermeister sales.
That's our life, the big wheel of shit. - The Fat Man, Blue Tango Salvage
The real causative in winter babies is that babies born under winter's astrological signs have shorter lifelines.
I see the explanation in the fact that married and educated women have sex with their man only once a year during their holiday in July/August. :)
I wonder if all the data comes from the North Hemisphere? What happens in the south?
The age cutoff for entry to kindergarten seems to cycle around mid-September, but varies quite a bit from state to state. But in general, a kid born in the winter will have to wait longer to start school.
> Unwed? What is this, 1950?
Statistically, the marital status of the parents is highly relevant to the child's prospects. Children whose parents are married to one another from prior to conception clear through until the child is an adult get on average much better grades in school, are significantly more likely to consistently hold down jobs as adults, make more money on average, are significantly less likely to have a criminal record, are less likely to be smokers, and so on and so forth. These are quite strong correlations.
Now, correlation is not causation. It's possible that the parent's strong marriage does not *cause* the child's good prospects and performance, but rather that both are caused by some of the same socioeconomic factors. But it's still very much relevant in a statistical study like this.
Cut that out, or I will ship you to Norilsk in a box.
I was born in December and pursuing double masters with GPA of 3.4 is it really bad?
I was born in June, and received a Ph.D by the time I was 27, with a 3.95 GPA. Luckily for me, part of that Ph.D training involved learning that the word data is not the plural of anecdote.
It's a good thing, too, because your comment might otherwise serve as the first brick in the foundation of my claim that summer babies are caustic and monumental shitheads that seem to spend their free time in pissing matches.
suppose educated women (and education strongly correlates wit income and wealth) "know" htat babies are supposed to be born in the spirng.....
this would rduce the whole thing to a cultural artifact: well to do parents tell thier kids to have a spring baby, and so it goes...
Now, correlation is not causation. It's possible that the parent's strong marriage does not *cause* the child's good prospects and performance, but rather that both are caused by some of the same socioeconomic factors
I like the idea that it's actually a reverse correlation- that stupid children with poor prospects and bad grades cause their parents' divorces.
Sigh. Correlation means one of three things with regard to causation. In this case those are:
a) being born in the winter causes increased risk of health and education problems for the baby
b) the baby's increased risk of health and education problems causes him or her to be born in the winter (clearly ridiculous)
c) a third factor causes the baby to both be born in the winter and have increased risk of health and education problems.
The correlation between birth month and risk of health and education problems has been observed. This study is pointing out that the direct causative option (a) is probably not true since they have found possible third factors (c) that appear to influence birth month and are known to have an effect on the risk of health and education problems.
In other words, the study is saying, with actual data and without the childish, misunderstood slogans, the same thing you are - birth month does not cause increased risk of health and education problems.
Showing correlation is required for establishing a causative link between two observations so no, correlation studies do not "need to die." It would be nice if people (including you) understood them a little better though.