I have not posted here in a while. This is mostly due to the fact that I have a job that is both engaging and demanding. I started this blog as a way to blow off steam, but I realized this mostly meant ranting about those fools at the academy! of whom there are indeed plenty. These are reality based rants, but I’ve got better things to do.
As it happens, I’ve come down with a bug that keeps me at home but leaves just enough energy to read and type, but little else. This is an excellent recipe for inciting a rant. Reading the Washington Post article on delayed gratification in children brings it on.
It is not really the article that gets me, let alone the scholarly paper on which it is based. I have not read the latter, and have no intention of doing so. I hope its author has thought through the interpretation better than is implied by what I see in the WaPo article. That is easy for me to believe; my own experience is that what academics say to the press has little to do with what eventually appears in the press – sometimes even inverting its meaning outright. (At one point I was quoted as saying that dark matter experimentalists should give up, when what I had said was that it was important to pursue these experiments to their logical conclusion, but that we also needed to think about what would constitute a logical conclusion if dark matter remains undetected.)
So I am at pains to say that my ire is not directed at the published academic article. In this case it isn’t even directed at the article in the WaPo, regardless of whether it is a fair representation of the academic work or not. My ire is directed entirely at the interpretation of a single graph, which I am going to eviscerate.
The graph in question shows the delay time measured in psychology experiments over the years. It is an attempt to measure self-control in children. When presented with a marshmallow but told they may have two marshmallows if they wait for it, how long can they hold out? This delayed gratification is thought to be a measure of self-control that correlates positively with all manners of subsequent development. Which may indeed be true. But what can we learn from this particular graph?
The graph plots the time delay measured from different experiments against the date of the experiment. Every point (plotted as a marshmallow – cute! I don’t object to that) represents an average over many children tested at that time. Apparently they have been “corrected” to account for the age of the children (one gets better at delayed gratification as one matures) which is certainly necessary, but it also raises a flag. How was the correction made? Such details can matter.
However, my primary concern is more basic. Do the data, as shown, actually demonstrate a trend?
To answer this question for yourself, the first thing you have to be able to do is mentally remove the line. That big black bold line that so nicely connects the dots. Perhaps it is a legitimate statistical fit of some sort. Or perhaps it is boldface to [mis]guide the eye. Doesn’t matter. Ignore it. Look at the data.
The first thing I notice about the data are the outliers – in this case, 3 points at very high delay times. These do not follow the advertised trend, or any trend. Indeed, they seem in no way related to the other data. It is as if a different experiment had been conducted.
When confronted with outlying data, one has a couple of choices. If we accept that these data are correct and from the same experiment, then there is no trend: the time of delayed gratification could be pretty much anything from a minute to half an hour. However, the rest of the data do clump together, so the other option is that these outliers are not really representing the same thing as the rest of the data, and should be ignored, or at least treated with less weight.
The outliers may be the most striking part of the data set, but they are usually the least important. There are all sorts of statistical measures by which to deal with them. I do not know which, if any, have been applied. There are no error bars, no boxes representing quartiles or some other percentage spanned by the data each point represents. Just marshmallows. Now I’m a little grumpy about the cutesy marshmallows. All marshmallows are portrayed as equal, but are some marshmallows more equal than others? This graph provides no information on this critical point.
In the absence of any knowledge about the accuracy of each marshmallow, one is forced to use one’s brain. This is called judgement. This can be good or bad. It is possible to train the brain to be a good judge of these things – a skill that seems to be in decline these days.
What I see in the data are several clumps of points (disregarding the outliers). In the past decade there are over a dozen points all clumped together around an average of 8 minutes. That seems like a pretty consistent measure of the delayed gratification of the current generation of children.
Before 2007, the data are more sparse. There are a half a dozen points on either side of 1997. These have a similar average of 7 or 8 minutes.
Before that there are very little data. What there is goes back to the sixties. One could choose to see that as two clumps of three points, or one clump of six points. If one does the latter, the mean is around 5 minutes. So we had a “trend” of 5 minutes circa 1970, 7 minutes circa 1997, and 8 minutes circa 2010. That is an increase over time, but it is also a tiny trend – much less persuasive than the heavy solid line in the graph implies.
If we treat the two clumps of three separately – as I think we should, since they sit well apart from each other – then we have to choose which to believe. They aren’t consistent. The delay time in 1968 looks to have an average of two minutes; in 1970 it looks to be 8 minutes. So which is it?
According to the line in the graph, we should believe the 1968 data and not the 1970 data. That is, the 1968 data fall nicely on the line, while the 1970 data fall well off it. In percentage terms, the 1970 data are as far from the trend as the highest 2010 point that we rejected as an outlier.
When fitting a line, the slope of the line can be strongly influence by the points at its ends. In this case, the earliest and the latest data. The latest data seem pretty consistent, but the earliest data are split. So the slope depends entirely on which clump of three early points you choose to believe.
If we choose to believe the 1970 clump, then the “trend” becomes 8 minutes in 1970, 7 minutes in 1997, 8 minutes in 2010. Which is to say, no trend at all. Try disregarding the first three (1968) points and draw your own line on this graph. Without them, it is pretty flat. In the absence of error bars and credible statistics, I would conclude that there is no meaningful trend present in the data at all. Maybe a formal fit gives a non-zero slope, but I find it hard to believe it is meaningfully non-zero.
None of this happens in a vacuum. Lets step back and apply some external knowledge. Have people changed over the 5 decades of my life?
The contention of the WaPo article is that they have. Specifically, contrary to the perception that iPhones and video games have created a generation with a cripplingly short attention span (congrats if you made it this far!), in fact the data show the opposite. The ability of children to delay gratification has improved over the time these experiments have been conducted.
What does the claimed trend imply? If we take it literally, then extrapolating back in time, the delay time goes to zero around 1917. People in the past must have been completely incapable of delaying gratification for even an instant. This was a power our species only developed in the past century.
I hope that sounds implausible. If there is no trend, which is what the data actually show, then children a half century ago were much the same as children a generation ago are much the same as the children of today. So the more conservative interpretation of the graph would be that human nature is rather invariant, at least as indicated by the measure of delayed gratification in children.
Sadly, null results are dull. There well may be a published study reporting no trend, but it doesn’t get picked up by the Washington Post. Imagine the headline: “Children today are much the same as they’ve always been!” Who’s gonna click on that? In this fashion, even reputable news sources contribute to the scourge of misleading science and fake news that currently pollutes our public discourse.
This sort of over-interpretation of weak trends is rife in many fields. My own, for example. This is why I’m good at spotting them. Fortunately, screwing up in Astronomy seldom threatens life and limb.
Then there is Medicine. My mother was a medical librarian; I occasionally browsed their journals when waiting for her at work. Graphs for the efficacy of treatments that looked like the marshmallow graph were very common. Which is to say, no effect was in evidence, but it was often portrayed as a positive trend. They seem to be getting better lately (which is to say, at some point in the not distant past some medical researchers were exposed to basic statistics), but there is an obvious pressure to provide a treatment, even if the effect of the available course of treatment is tiny. Couple that to the aggressive marketing of drugs in the US, and it would not surprise me if many drugs have been prescribed based on efficacy trends weaker than seen in the marshmallow graph. See! There is a line with a positive slope! It must be doing some good!
Another problem with data interpretation is in the corrections applied. In the case of marshmallows, one must correct for the age of the subject: an eight year old can usually hold out longer than a toddler. No doubt there are other corrections. The way these are usually made is to fit some sort of function to whatever trend is seen with age in a particular experiment. While that trend may be real, it also has scatter (I’ve known eight year olds who couldn’t out wait a toddler), which makes it dodgy to apply. Do all experiments see the same trend? It is safe to apply the same correction to all of them? Worse, it is often necessary to extrapolate these corrections beyond where they are constrained by data. This is known to be dangerous, as the correction can become overlarge upon extrapolation.
It would not surprise me if the abnormally low points around 1968 were over-corrected in some way. But then, it was the sixties. Children may have not changed much since then, but the practice of psychology certainly has. Lets consider the implications that has for comparing 1968 data to 2017 data.
The sixties were a good time for psychological research. The field had grown enormously since the time of Freud and was widely respected. However, this was also the time when many experimental psychologists thought psychotropic drugs were a good idea. Influential people praised the virtues of LSD.
My father was a grad student in psychology in the sixties. He worked with swans. One group of hatchlings imprinted on him. When they grew up, they thought they should mate with people – that’s what their mom looked like, after all. So they’d and make aggressive displays towards any person (they could not distinguish human gender) who ventured too close.
He related the anecdote of a colleague who became interested in the effect of LSD on animals. The field was so respected at the time that this chap was able to talk the local zoo into letting him inject an elephant with LSD. What could go wrong?
Perhaps you’ve heard the expression “That would have killed a horse! Fortunately, you’re not a horse.” Well, the fellow in question figured elephants were a lot bigger than people. So he scaled up the dose by the ratio of body mass. Not, say, the ratio of brain size, or whatever aspect of the metabolism deals with LSD.
That’s enough LSD to kill an elephant.
Sad as that was for the elephant, who is reputed to have been struck dead pretty much instantly – no tripping rampage preceded its demise – my point here is that these were the same people conducting the experiments in 1968. Standards were a little different. The difference seen in the graph may have more to do with differences in the field than with differences in the subjects.
That is not to say we should simply disregard old data. The date on which an observation is made has no bearing on its reliability. The practice of the field at that time does.
The 1968 delay times are absurdly low. All three are under four minutes. Such low delay times are not reproduced in any of the subsequent experiments. They would be more credible if the same result were even occasionally reproduced. It ain’t.
Another way to look at this is that there should be a comparable number of outliers on either side of the correct trend. That isn’t necessarily true – sometimes systematic errors push in a single direction – but in the absence of knowledge of such effects, one would expect outliers on both the high side and the low side.
In the marshmallow graph, with the trend as drawn, there are lots of outliers on the high side. There are none on the low side. [By outlier, I mean points well away from the trend, not just scattered a little to one side or the other.]
If instead we draw a flat line at 7 or 8 minutes, then there are three outliers on both sides. The three very high points, and the three very low points, which happen to occur around 1968. It is entirely because the three outliers on the low side happen at the earliest time that we get even the hint of a trend. Spread them out, and they would immediately be dismissed as outliers – which is probably what they are. Without them, there is no significant trend. This would be the more conservative interpretation of the marshmallow graph.
Perhaps those kids in 1968 were different in other ways. The experiments were presumably conducted in psychology departments on university campuses in the late sixties. It was OK to smoke inside back then, and not everybody restricted themselves to tobacco in those days. Who knows how much second hand marijuana smoke was inhaled just to getting to the test site? I jest, but the 1968 numbers might just measure the impact on delayed gratification when the subject gets the munchies.
6 thoughts on “The kids are all right, but they can’t interpret a graph”
Thanks again for highlighting the importance of correctly intepreting statistical graphs.I am interested in the importance of the outliers on the baryonic tully fisher relationship. What are they telling us? Surely there must be another parameter at work to explain their outlier properties which we are currently unaware of.
As you say, you’d thing there would be some second parameter, like radius or environment. But as best I can tell, there are no genuine outliers from the baryonic Tully-Fisher relation. Outliers in the “this case is messed up,” of course. But I’ve spent the better part of a career looking for genuine physical deviations, and found zero convincing cases.
(sorry for possible duplicates)
Please, we like the steam blowing ! though this description probably doesn’t do justice to the other important facets of your blog – history of science, exposition of current astrophysics and cosmology. Those are much appreciated.
About delayed gratification: this is typical. I should start by saying I think there are real reasons to do experimental psychology. It has a legitimate place in the scientific world, even now with the explosion of neuroscience, in attempting to describe the objects and mechanisms in our minds that drive our behaviors.
What simply cannot be justified is the way exp. psy is done in 2017. The statistical standards are ridiculous, as you have illustrated, but it goes even deeper. Even when an analysis of variance is carried out, the gold standard remains anovas with p-values at the 0.05 level. The number of subjects for any given experiment is usually between 20 and 40, dangerously low. Most experiments are not pre-registered, so the experimenter can change the parameters at will without reporting on these “early” results. It’s called “piloting” a study. As a result of those practices, the field has almost the lowest replicability rate of all the sciences, and the bias towards publishing positive results is terrible. (see e.g. https://www.nature.com/news/replication-studies-bad-copy-1.10634 )
Hope you feel better soon!
Oh, the look of disappointment on that little boy’s face! I guess we get back what we do to them.
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