Does race or profession affect sleep?

/ bs king / 3 Comments

I’ve commented before on my skepticism about self reported sleep studies.

Two recent studies on sleep piqued my interest, and while my original criticisms hold, there was yet another issue I wanted to bring up.

The first was from a few months back at the NYT blog, commenting on the most sleep deprived professions.
The second is from Time magazine, and talks about sleep differences among the races.

My gripe with both studies is the extremely small difference between the rankings.

In the professions study (sponsored by Sleepy’s btw), the most sleep deprived profession (home health aide) clocks in at 6hr57m.  The most well rested is loggers, with 7h20m.   On a self reported survey, how significant is 23 minutes?

From the study on races:

Overall, the researchers found, blacks, Hispanics and Asians slept less than whites. Blacks got 6.8 hours of sleep a night on average, compared with 6.9 hours for Hispanics and Asians, and 7.4 hours a night for whites. 

Here we see the same thing….there’s a 6 minute difference between the totals for Blacks and Hispanics and Asians.   Whites get 30 minutes more than Hispanics/Asians and 36 minutes more than blacks.

I question the significance of this, since I can’t remember whether I went to bed at 9:00 or 9:30 last night, and would have to guess if someone asked me.  Both surveys state this was self reported, and thus the chance these averages could be even closer together is huge.

Additionally, these differences do not actually reach the level of significance that the studies showing the dangers of sleep deprivation reach.

For example, in this study about sleep and overeating, subjects were woken up 2/3rds of the way through their normal sleep time.  That would be 2 hours early for nearly everyone above.  The studies on heart disease were only linked with chronic insomnia.  Cancer and diabetes are both more common in shift workers, but as someone who worked overnights for 3 years, I can tell you that’s not the same as waking up 30 minutes early.

Kaiser Fung has a great post about the popularizing of tiny effects that will be a hit if you didn’t like Freakonomics.

Stats and Father’s and Father’s Day Stats

/ bs king / 5 Comments

I spent most of yesterday driving back from somewhere on the Pennsylvania/Maryland/West Virginia border, so I didn’t have time to do a proper Father’s Day post.  I did call my dad though, so I guess I get half credit.

I wanted to do a post for my father, because he’s pretty responsible for my love of stats.  If someone uncovers a stats gene some day, I got that from him too.  He’s the only other person I know who truly finds numbers and stats a great way to unwind.  He’s also the first person who I ever remember telling me to be more careful about how I read research.
As I recall, I was probably about 13 or 14, and someone had just told me that those from lower socioeconomic classes tended to score lower on the SATs.  I repeatedly this to my father, as I was outraged as only a teenage girl can be.  My father stopped me immediately and started explaining to me that socioeconomic status is not random, and therefore this may not be as bad as it looked.  College educated people would be likely to earn more and to also have children more likely to perform well on the SATs.  Whether this was a product of genetics or a general household emphasis, both nature and nurture would likely be stacked in favor of higher incomes.  We then had a nice long talk about school districts and testing bias, but he cautioned me strongly to remember that even if those situations were made perfectly equitable, higher income kids would like still score higher.  
It’s not often that a single conversation changes your outlook so completely, but that one did.  Here we are a decade and a half later, and looking for faults in studies is still a good chunk of what goes through my head on a daily basis.  Luckily for me, I had lots of people in my life who valued truth and intellectual integrity over agenda, but my dad is the first one I remember pushing this in a way that stuck.  
My Dad is the best example I have of someone who would actually repeat or acknowledge research that contradicted his own personal beliefs.  He taught us that a win doesn’t count if you have to distort the truth to get there.  I am eternally grateful for my Dad, and all the things he added to my life, statistically and otherwise.
To show my thanks, Dad, here are some numbers for you:

These show how important it is to have a dad.  
This is some census data about dads in America.
Here’s a link to the Sabermetrics for the current Red Sox team.

So happy Father’s Day dad, I sincerely hope that your emotional and mental state were at least one standard deviation above the median on a normalized scale.  Preferably two, even when adjusted for weekend vs weekday averages.

Soda bans and research misapplications

/ bs king / 3 Comments

When I first read about Mayor Bloomberg’s proposed soda restrictions for NYC, I immediately thought of this post where I mentioned the utter failure of removing vending machines from schools.  Thus, I was extremely skeptical that this ban would work at all, and it seemed quite an intrusion in to private business for what I saw as an untested theory.

To be honest, I didn’t put much more thought in to it.  I saw the studies about people eating more from large containers floating around, but I dismissed on the basis that (like with the vending machine theory) they were skipping a crucial step.  Even if this ban got people to drink less soda, that doesn’t actually prove it would reduce obesity.  You have to prove all the steps in the series to prove the conclusion.

A few days ago, the authors of the “bigger containers cause people to eat more” study published their own rebuttal to the ban.  In an excellent example of the clash of politics and research, they claim that to apply their work on portion sizes in this manor is a misreading of the body of their work.  They highlight that the larger containers study was done by assigning portion sizes at random, to subjects who had no expectations as to what they would be getting.  In their words, the ban is a problem because (highlight mine):

Banning larger sizes is a visible and controversial idea. If it fails, no one will trust that the next big — and perhaps better — idea will work, because “Look what happened in New York City.” It poisons the water for ideas that may have more potential.

Second, 150 years of research in food economics tells us that people get what they want. Someone who buys a 32-ounce soft drink wants a 32-ounce soft drink. He or she will go to a place that offers fountain refills, or buy two. If the people who want them don’t have much money, they might cut back on fruits or vegetables or a bit of their family meal budget.

In essence, by removing the random element and forcibly replacing what people want with something the don’t, you frequently will have the worst possible effect: rebellion.

Mindless eating can be a problem, but rebellious eating is even worse.

When the researchers you’re trying to use to back yourself up start protesting your policies, you know you got it all wrong.

It’s all (culturally) relative

/ bs king

Last week I put up a post regarding a study on sexism levels in men whose wives stay at home.  I argued that due to the diversity of that group of men, and the variety of reasons a woman might stay home, this study was essentially meaningless.

Another issue came up in the comments section that I wanted to touch on: cultural relevance of data.

Most studies that get press here in the US are from the US, performed on American subjects.  This is sketchy business.

In the study about stay at home moms, mothers who worked part time were lumped in with the stay at home mothers.  Interestingly, in the Netherlands, this would actually be 90% of the women.  Does that mean that nearly every Dutch man married to a woman is more likely to be sexist?  Or does it mean that part time work has different value in different cultures?

I took a look around for some other examples, and found that in China, many women see working as part of a new found freedom.  At a conference I attended a few months ago, I talked to a man from Shanghai who mentioned that his wife went back to work because she couldn’t have handled trying to fight off the two grandmother’s, both of whom wanted to watch the child.  Due to the one child policy, this was the only chance they would get to have a grandbaby.  In many ways, it was actually the hierarchical/patriarchal culture there that pushed his wife to go back to work, as opposed to having her stay home.  

As the world continues to flatten out, and as America continues to welcome new immigrants, we must be conscious of who studies are actually looking at and how generalizable the results are.  In the sexism study, even the authors admitted their findings were meant to be a commentary on the US only….but it should raise some questions that they seemed to be chasing after a structure that doesn’t exist in some very liberal countries.

Something to consider, depending on the goal of the study.

How long do you study to become one of the cultural elite?

/ bs king / 6 Comments

I took one class on assessment in my master’s, and it gave me a whole new respect for teachers (or anyone who routinely prepares questionnaires for people).

Figuring out how to assess whatever topic you’re assessing is really really hard.

That being said, I found this quiz particularly interesting.  It’s called “Do You Live In a Bubble?”, but it’s target is particularly the “new upper class” and how much they do or do not understand about the lives of most Americans.

What he chose to assess is fairly interesting….people you know, where you’ve lived, smoking and drinking patterns, jobs you’ve had, knowledge of popular media, etc.  Lots of interesting issues to be taken with those categories, especially for those who clearly didn’t get the score they were hoping for.  The comments are pretty amusing actually…I feel like one of the questions should have been “is it important to you that this quiz tell you that you are “of the people”?

The most interesting point here was actually the entire purpose of the quiz.  The author of the quiz answered a few follow up questions, but I thought this was the most telling one:

2. Do you feel that people scoring higher on the quiz are not culturally sequestered as well? 

Question from Reddit: HillbillyThinkTank[S]: “You’re right that everyone lives in a bubble of some kind; the tendency to cluster with similarly situated people is not a behavior limited to the “elite.” The way the quiz is structured, he is suggesting that a low-scoring person is culturally sequestered in a way that a high scoring person is not. I don’t think I agree with that.” 

Sure, they’re sequestered. We all live in bubbles of one kind or another. The problem is an asymmetry. As I put it in the book, it isn’t a problem if a truck driver doesn’t understand the priorities of a Yale law professor, or news anchor, or cabinet secretary. It’s a problem if the ignorance is the other way around, because the elites are busily affecting the lives of everyone else. When they haven’t the slightest idea what the rhythms and feel of life are like in mainstream America, they tend to make mistakes.

I thought this was an interesting case of trying measure a very abstract concept through concrete questioning.  He includes an explanation of each question and why it was included.

Agree or not with his questions, it certainly succeeds at being provocative.

Also, in case you’re curious, I scored a 56.

Weekend moment of Zen 6-9-12

/ bs king / 2 Comments

If you are a baseball fan who hasn’t yet read Mark Lisanti’s “Derek Jeter’s Diary” over at Grantland yet, go now.  Enjoy.

Though I don’t often do sports stats, “Jeter” has a few words about stats blogs:

I don’t read those blogs, they’re just negativity disguised as indisputable math…

That does about sum it up Derek.  I kind of want that stitched on a pillow.

He also has some words of wisdom on the limitations of statisticss:

The stats guys are always trying to tell you there’s no such thing as clutch, that there’s no special skill to it, it’s all probabilities and math. Look: I also know that math exists. I’ve taken math classes, I’ve seen numbers be added and subtracted in front of my very eyes. Those symbols on the back of baseball cards mean something real.  

But you can’t tell me that there’s not some magic ability some players have that makes them rise to the occasion when it counts most. I’ve seen Alex Rodriguez fail in huge situations too many times not to believe what I have is special. 

Have a good weekend everyone!

Sexism and stay at home moms

/ bs king / 10 Comments

I was just thinking I wanted to find a good marriage and family research paper to sink my teeth in to.

This one came across my inbox today, and I didn’t have to get much further than the abstract before I knew it was going to be a doozy.  Read for yourself:

In this article, we examine a heretofore neglected pocket of resistance to the gender revolution in the workplace: married male employees who have stay-at-home wives. We develop and empirically test the theoretical argument suggesting that such organizational members, compared to male employees in modern marriages, are more likely to exhibit attitudes, beliefs, and behaviors that are harmful to women in the workplace.

*Bias Alert*
My mother was a stay at home mom.  Therefore my father would have qualified for this study, and it is hard for me to even read their hypothesis without remembering that.  I happen to credit my father with giving me my passion for statistics and data analysis, and he has never once discouraged me from doing anything I wanted to professionally (with the exception of when I mentioned law school….that he soundly discouraged as a waste of talent….and this was  15 years before anyone was talking about a law school bubble).  I will not go in to all the details of my parents marriage here, but I doubt you could find anyone who would call my parents marriage anything less than an equal partnership focused on doing what was best for the family.

As an extra level of bias, I will be continuing my (full-time) job post baby.
*End Alert*

I’ve noticed a disturbing trend in both the general population and academic research: people seem to get very hung up on conflating “stay at home mom” with “traditional marriage”.  The study authors do this openly….they admit that they classify a marriage as “modern” based solely on whether or not the wife works full time.  The only criteria for “traditional” is that she doesn’t work at all, and part time work is all classified as “neo-traditional”.

To ignore the economic realities that drive families to make decisions about work seems to me to be an immense oversight.  I have met plenty of stay at home mothers who were in very equitable marriages, and I have met quite a few working mothers whose primary source of stress was their husbands continued expectation that they were still responsible for all child care/household duties.  I believe that using only one metric to rank a marriage as “traditional” or “modern” is a horrible over generalization….especially since most women with small children would prefer to work part time.  In fact (from the Pew study):

The public is skeptical about full-time working moms. Just 14% of men and 10% of women say that a full-time job is the “ideal” situation for a woman who has a young child. A plurality of the public (44%) say a part-time job is ideal for such a mother, while a sizable minority (38%) say the ideal situation is for her not to work outside the home at all.

So 90% of women don’t think the “modern” setup is ideal when there are young children involved.  If one of these women than chooses to stay home with her kids, has her husband truly regressed from “modern” to “traditional”?

For both the economic reasons and the “women’s choice” reasons, I reject studies that try to tie stay at home motherhood to anything else.  The sample is just too broad, and the reasons too varied.  It also undermines exactly how expensive child care can be….by my estimate, my mom would have had to bring home at least $4000 a month (in today’s dollars)  to pay for child care for 4 children.  $4000 after tax is a pretty hefty before tax salary.

I don’t argue that personal life can affect professional attitudes, and I would never advocate for sexism in the workplace.  In this study however, I really had to question the motives.  Is it really the best idea to fight gender stereotypes with stereotypes about very broad choices?  Is the point here that the workplace will only be fair when women participate as much as men?  Isn’t it a bit sexist to totally disregard the role women play in the decision to work or not work?  Shouldn’t we all just be able to do what’s best for our families, no questions asked?

Quote of the week and more recall coverage

/ bs king / 2 Comments

Statistics are like bikinis.  What they reveal is suggestive, but what they conceal is vital.  ~Aaron Levenstein


I’ve been reading more of the Scott Walker recall election coverage, and was struck by the frequent references to Walker being “the first governor to survive a recall election”.  Of course this made me curious how many governor’s had been recalled.  I remembered the California governor a few years back, so I had been imagining it would be at least a dozen or so.

Nope.

It’s two.  Lynn Frazier from North Dakota in 1921, and Gray Davis from California in 2003.

I had to laugh at my own sampling bias.  My assumptions were pretty understandable….I’ve been of voting age since 1999, and in that time this has happened twice.  Therefore it was reasonable to assume this happened at least occasionally.   I figured about once every 10 years, which would be 23 or 24 in American history.  I was pretty sure not every state had a recall option, so I halved it.  12 felt good.

This is the problem when data leaves out key points….it relies on our own assumptions to fill in the details.  Engineers are normally trained to get explicit with their assumptions when estimating, as evidenced by the famous Fermi problem.  However, even the most carefully thought through assumptions are still guesses.

That’s why it’s important to remember the quote above: what you’re shown is important, but it’s not half as interesting as what’s hidden.