Category: Education • Statistics
Since I've been writing a lot about education, I have some brief thoughts about the NY Times report by David Leonhardt about some findings from Tennessee's Project STAR which tracked the long-term outcomes about a randomization trial of kindergartners (slides from a presentation are available as a pdf):
Just as in other studies, the Tennessee experiment found that some teachers were able to help students learn vastly more than other teachers. And just as in other studies, the effect largely disappeared by junior high, based on test scores. Yet when Mr. Chetty and his colleagues took another look at the students in adulthood, they discovered that the legacy of kindergarten had re-emerged.
Students who had learned much more in kindergarten were more likely to go to college than students with otherwise similar backgrounds. Students who learned more were also less likely to become single parents. As adults, they were more likely to be saving for retirement. Perhaps most striking, they were earning more.
All else equal, they were making about an extra $100 a year at age 27 for every percentile they had moved up the test-score distribution over the course of kindergarten. A student who went from average to the 60th percentile -- a typical jump for a 5-year-old with a good teacher -- could expect to make about $1,000 more a year at age 27 than a student who remained at the average. Over time, the effect seems to grow, too.
First, my reading of the presentation is that the jump is only around $500 per year (see slide #46); ironically, the $1,000 increase is attributed to teacher seniority (see slide #33). Second, the researchers admit that they can't distinguish between the influence of the teacher and of their peers in the class (slide #39)--to claim that "some teachers were able to help students learn vastly more than other teachers" is not supported by the experimental design.
But there are other issues too:
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Posted by Mike at 12:27 PM • 0 Comments • 0 TrackBacks
Category: Education • Massachusetts • Statistics
Yesterday, I described the relationship between low-income and poor performance in English and math in Massachusetts (see the post for methodological details). Well, I've saved the worst for last--science education:

Just to remind everyone, the horizontal axis is the percentage of children in a school who qualify for free lunch, and the vertical axis is the percentage of children who, according to their MCAS scores, are either classified as "Need Improvement" or "Warning/Failing" in science.
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Posted by Mike at 9:58 AM • 9 Comments • 0 TrackBacks
Category: Bidness
Or, for that matter, jumping into the water with financial sharks under any circumstances. The NY Times has an article about the ongoing legal trials of David H. Brooks, the chief executive and chairman of a body-armor company. The article primarily focuses on what a loathsome piece of shit Brooks is: not only did he rip off investors and the U.S. government, but his body armor doesn't work as advertised in hot weather. Which would be fine if we were engaged with Al-Queda...in Iceland.
But this section at the end caught my attention (italics mine):
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Posted by Mike at 12:16 PM • 4 Comments • 0 TrackBacks
Category: Education • Massachusetts • Statistics
I've described before how there is a significant correlation between poverty and educational performance when we use state-level data. But as I pointed out, one of the interesting things is that the residual--the difference between the expected scores for a given state and the actual scores--can be quite large for some states (e.g., Massachusetts does much better than expected, Arkansas much worse). We can learn a lot from these differences (i.e., what does MA do differently from Arkansas). But if we look at only one state, can we determine what the effect of poverty is?
To do this, I've pulled the MCAS test data, which has both the test scores and student demographic information broken down by school (and district). I've decided to focus on 10th grade scores, and MA reports scores for math, English, and science. Before we get to the findings, I'll give a brief outline of some of the caveats, data decisions, and so on. To start with, I'm using the 2009 reported data. While no standardized test is perfect, the MCAS is better than many: we haven't seen the doubling and trebling of these scores, as has been observed in other states*. Because these tests have been instituted for a long time, we have a good idea of what they test. Also, since these scores are from the same year, we have controlled for the 'lousy' test effect--even if the test isn't perfect, all students receive the same test (obviously, if the test is ludicrous, such as nearly everyone fails, then there are issues).
A bit more about methodology, then...dataz!
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Posted by Mike at 10:04 AM • 3 Comments • 0 TrackBacks
Category: Conservatives • Global Warming • The War on Science
Well, we can always hope. In a recent column about global warming, Paul Krugman makes this ancillary point (italics mine):
Nor is this evidence tainted by scientific misbehavior. You've probably heard about the accusations leveled against climate researchers -- allegations of fabricated data, the supposedly damning e-mail messages of "Climategate," and so on. What you may not have heard, because it has received much less publicity, is that every one of these supposed scandals was eventually unmasked as a fraud concocted by opponents of climate action, then bought into by many in the news media. You don't believe such things can happen? Think Shirley Sherrod
Krugman continues:
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Posted by Mike at 1:03 PM • 2 Comments • 0 TrackBacks
Category: Antibiotics • Genomics
So, in some quarters, there's been wailing and gnashing of teeth over the Congressional hearings about the direct-to-customer ('DTC') genetic testing industry. I've discussed why I don't think regulation is a disaster before, but I'll add one more issue to the mix: maintaining subject confidentiality in NIH genomic studies. If someone related to a person in a study publicly releases his or her genome, it could be possible to identify a 'deidentified' anonymous subject. I'm curious to see how that issue shakes out.
But that's not what this post is about. Instead, I propose that the DTC genetic testing industry should follow the path set by antibiotic susceptibility testing--the laboratory processes used to determine if bacteria are resistant to antibiotics.
First, the DTC industry has to realize that they are in the medical testing device business.
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Posted by Mike at 10:08 AM • 0 Comments • 0 TrackBacks