the APS likes me!

Somehow I wound up profiled in this month’s issue of the APS Observer as a “Rising Star“. I’d like to believe this means I’m a really big deal now, but I suspect what it actually means is that someone on the nominating committee at APS has extraordinarily bad judgment. I say this in no small part because I know some of the other people who were named Rising Stars quite well (congrats to Karl Szpunar,  Jason Chan, and Alan Castel, among many other people!), so I’m pretty sure I can distinguish people who actually deserve this from, say, me.

Of course, I’m not going to look a gift horse in the mouth. And I’m certainly thrilled to be picked for this. I know these things are kind of a crapshoot, but it still feels really nice. So while the part of my brain that understands measurement error is saying “meh, luck of the draw,” that other part of my brain that likes to be told it’s awesome is in the middle of a three day coke bender right now*. The only regret both parts of the brain have is that there isn’t any money attached to the award–or even a token prize like, say, a free statistician for a year. But I don’t think I’m going to push my luck by complaining to APS about it.

One thing I like a lot about the format of the Rising Star awards is they give you a full page to talk about yourself and your research. If there’s one thing I like to talk about, it’s myself. Usually, you can’t talk about yourself for very long before people start giving you dirty looks. But in this case, it’s sanctioned, so I guess it’s okay. In any case, the kind folks at the Observer sent me a series of seven questions to answer. And being an upstanding gentleman who likes to be given fancy awards, I promptly obliged. I figured they would just run what I sent them with minor edits… but I WAS VERY WRONG. They promptly disassembled nearly all of my brilliant observations and advice and replaced them with some very tame ramblings. So if you actually bother to read my responses, and happen to fall asleep halfway through, you’ll know who to blame. But just to set the record straight, I figured I would run through each of the boilerplate questions I was asked, and show you the answer that was printed in the Observer as compared to what I actually wrote**:

What does your research focus on?

What they printed: Most of my current research focuses on what you might call psychoinformatics: the application of information technology to psychology, with the aim of advancing our ability to study the human mind and brain. I’m interested in developing new ways to acquire, synthesize, and share data in psychology and cognitive neuroscience. Some of the projects I’ve worked on include developing new ways to measure personality more efficiently, adapting computer science metrics of string similarity to visual word recognition, modeling fMRI data on extremely short timescales, and conducting large-scale automated synthesis of published neuroimaging findings. The common theme that binds these disparate projects together is the desire to develop new ways of conceptualizing and addressing psychological problems; I believe very strongly in the transformative power of good methods.

What I actually said: I don’t know! There’s so much interesting stuff to think about! I can’t choose!

What drew you to this line of research? Why is it exciting to you?

What they printed: Technology enriches and improves our lives in every domain, and science is no exception. In the biomedical sciences in particular, many revolutionary discoveries would have been impossible without substantial advances in information technology. Entire subfields of research in molecular biology and genetics are now synonymous with bioinformatics, and neuroscience is currently also experiencing something of a neuroinformatics revolution. The same trend is only just beginning to emerge in psychology, but we’re already able to do amazing things that would have been unthinkable 10 or 20 years ago. For instance, we can now collect data from thousands of people all over the world online, sample people’s inner thoughts and feelings in real time via their phones, harness enormous datasets released by governments and corporations to study everything from how people navigate their spatial world to how they interact with their friends, and use high-performance computing platforms to solve previously intractable problems through large-scale simulation. Over the next few years, I think we’re going to see transformative changes in the way we study the human mind and brain, and I find that a tremendously exciting thing to be involved in.

What I actually said: I like psychology a lot, and I like technology a lot. Why not combine them!

Who were/are your mentors or psychological influences?

What they printed: I’ve been fortunate to have outstanding teachers and mentors at every stage of my training. I actually started my academic career quite disinterested in science and owe my career trajectory in no small part to two stellar philosophy professors (Rob Stainton and Chris Viger) who convinced me as an undergraduate that engaging with empirical data was a surprisingly good way to discover how the world really works. I can’t possibly do justice to all the valuable lessons my graduate and postdoctoral mentors have taught me, so let me just pick a few out of a hat. Among many other things, Todd Braver taught me how to talk through problems collaboratively and keep recursively questioning the answers to problems until a clear understanding materializes. Randy Larsen taught me that patience really is a virtue, despite my frequent misgivings. Tor Wager has taught me to think more programmatically about my research and to challenge myself to learn new skills. All of these people are living proof that you can be an ambitious, hard-working, and productive scientist and still be extraordinarily kind and generous with your time. I don’t think I embody those qualities myself right now, but at least I know what to shoot for.

What I actually said: Richard Feynman, Richard Hamming, and my mother. Not necessarily in that order.

To what do you attribute your success in the science?

What they printed: Mostly to blind luck. So far I’ve managed to stumble from one great research and mentoring situation to another. I’ve been fortunate to have exceptional advisors who’ve provided me with the perfect balance of freedom and guidance and amazing colleagues and friends who’ve been happy to help me out with ideas and resources whenever I’m completely out of my depth — which is most of the time.

To the extent that I can take personal credit for anything, I think I’ve been good about pursuing ideas I’m passionate about and believe in, even when they seem unlikely to pay off at first. I’m also a big proponent of exploratory research; I think pure exploration is tremendously undervalued in psychology. Many of my projects have developed serendipitously, as a result of asking, “What happens if we try doing it this way?”

What I actually said: Mostly to blind luck.

What’s your future research agenda?

What they printed: I’d like to develop technology-based research platforms that improve psychologists’ ability to answer existing questions while simultaneously opening up entirely new avenues of research. That includes things like developing ways to collect large amounts of data more efficiently, tracking research participants over time, automatically synthesizing the results of published studies, building online data repositories and collaboration tools, and more. I know that all sounds incredibly vague, and if you have some ideas about how to go about any of it, I’d love to collaborate! And by collaborate, I mean that I’ll brew the coffee and you’ll do the work.

What I actually said: Trading coffee for publications?

Any advice for even younger psychological scientists? What would you tell someone just now entering graduate school or getting their PhD?

What they printed: The responsible thing would probably be to say “Don’t go to graduate school.” But if it’s too late for that, I’d recommend finding brilliant mentors and colleagues and serving them coffee exactly the way they like it. Failing that, find projects you’re passionate about, work with people you enjoy being around, develop good technical skills, and don’t be afraid to try out crazy ideas. Leave your office door open, and talk to everyone you can about the research they’re doing, even if it doesn’t seem immediately relevant. Good ideas can come from anywhere and often do.

What I actually said: “Don’t go to graduate school.”

What publication you are most proud of or feel has been most important to your career?

What they printed: Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wager, T. D. (2011). Large-scale automated synthesis of human functional neuroimaging data. Manuscript submitted for publication.

In this paper, we introduce a highly automated platform for synthesizing data from thousands of published functional neuroimaging studies. We used a combination of text mining, meta-analysis, and machine learning to automatically generate maps of brain activity for hundreds of different psychological concepts, and we showed that these results could be used to “decode” cognitive states from brain activity in individual human subjects in a relatively open-ended way. I’m very proud of this work, and I’m quite glad that my co-authors agreed to make me first author in return for getting their coffee just right. Unfortunately, the paper isn’t published yet, so you’ll just have to take my word for it that it’s really neat stuff. And if you’re thinking, “Isn’t it awfully convenient that his best paper is unpublished?”… why, yes. Yes it is.

What I actually said: …actually, that’s almost exactly what I said. Except they inserted that bit about trading coffee for co-authorship. Really all I had to do was ask my co-authors nicely.

Anyway, like I said, it’s really nice to be honored in this way, even if I don’t really deserve it (and that’s not false modesty–I’m generally the first to tell other people when I think I’ve done something awesome). But I’m a firm believer in regression to the mean, so I suspect the run of good luck won’t last. In a few years, when I’ve done almost no new original work, failed to land a tenure-track job, and dropped out of academia to ride horses around the racetrack***, you can tell people that you knew me back when I was a Rising Star. Right before you tell them you don’t know what the hell happened.

———————————-

* But not really.

** Totally lying. Pretty much every word is as I wrote it. And the Observer staff were great.

*** Hopefully none of these things will happen. Except the jockey thing; that would be awesome.

CNS 2011: a first-person shorthand account in the manner of Rocky Steps

Friday, April 1

4 pm. Arrive at SFO International on bumpy flight from Denver.

4:45 pm. Approach well-dressed man downtown and open mouth to ask for directions to Hyatt Regency San Francisco. “Sorry,” says well-dressed man, “No change to give.” Back off slowly, swinging bags, beard, and poster tube wildly, mumbling “I’m not a panhandler, I’m a neuroscientist.” Realize that difference between the two may be smaller than initially suspected.

6:30 pm. Hear loud knocking on hotel room door. Open door to find roommate. Say hello to roommate. Realize roommate is extremely drunk from East Coast flight. Offer roommate bag of coffee and orange tic-tacs. Roommate is confused, asks, “are you drunk?” Ignore roommate’s question. “You’re drunk, aren’t you.” Deny roommate’s unsubstantiated accusations. “When you write about this on your blog, you better not try to make it look like I’m the drunk one,” roommate says. Resolve to ignore roommate’s crazy talk for next 4 days.

6:45 pm. Attempt to open window of 10th floor hotel room in order to procure fresh air for face. Window refuses to open. Commence nudging of, screaming at, and bargaining with window. Window still refuses to open. Roommate points out sticker saying window does not open. Ignore sticker, continue berating window. Window still refuses to open, but now has low self-esteem.

8 pm. Have romantic candlelight dinner at expensive french restaurant with roommate. Make jokes all evening about ideal location (San Francisco) for start of new intimate relationship. Suspect roommate is uncomfortable, but persist in faux wooing. Roommate finally turns tables by offering to put out. Experience heightened level of discomfort, but still finish all of steak tartare and order creme brulee. Dessert appetite is immune to off-color humor!

11 pm – 1 am. Grand tour of seedy SF bars with roommate and old grad school friend. New nightlife low: denied entrance to seedy dance club because shoes insufficiently classy. Stupid Teva sandals.

Saturday, April 2

9:30 am. Wake up late. Contemplate running downstairs to check out ongoing special symposium for famous person who does important research. Decide against. Contemplate visiting hotel gym to work off creme brulee from last night. Decide against. Contemplate reading conference program in bed and circling interesting posters to attend. Decide against. Contemplate going back to sleep. Consult with self, make unanimous decision in favor.

1 pm. Have extended lunch meeting with collaborators at Ferry Building to discuss incipient top-secret research project involving diesel generator, overstock beanie babies, and apple core. Already giving away too much!

3:30 pm. Return to hotel. Discover hotel is now swarming with name badges attached to vaguely familiar faces. Hug vaguely familiar faces. Hugs are met with startled cries. Realize that vaguely familiar faces are actually completely unfamiliar faces. Wrong conference: Young Republicans, not Cognitive Neuroscientists. Make beeline for elevator bank, pursued by angry middle-aged men dressed in American flags.

5 pm. Poster session A! The sights! The sounds! The lone free drink at the reception! The wonders of yellow 8-point text on black 6′ x 4′ background! Too hard to pick a favorite thing, not even going to try. Okay, fine: free schwag at the exhibitor stands.

5 pm – 7 pm. Chat with old friends. Have good time catching up. Only non-fictionalized bullet point of entire piece.

8 pm. Dinner at belly dancing restaurant in lower Haight. Great conversation, good food, mediocre dancing. Towards end of night, insist on demonstrating own prowess in fine art of torso shaking; climb on table and gyrate body wildly, alternately singing Oompa-Loompa song and yelling “get in my belly!” at other restaurant patrons. Nobody tips.

12:30 am. Take the last train to Clarksville. Take last N train back to Hyatt Regency hotel.

Sunday, April 3

7 am. Wake up with amazing lack of hangover. Celebrate amazing lack of hangover by running repeated victory laps around 10th floor of Hyatt Regency, Rocky Steps style. Quickly realize initial estimate of hangover absence off by order of magnitude. Revise estimate; collapse in puddle on hotel room floor. Refuse to move until first morning session.

8:15 am. Wander the eight Caltech aisles of morning poster session in search of breakfast. Fascinating stuff, but this early in morning, only value signals of interest are smell and sight of coffee, muffins, and bagels.

10 am. Terrific symposium includes excellent talks about emotion, brain-body communication, and motivation, but favorite moment is still when friend arrives carrying bucket of aspirin.

1 pm. Bump into old grad school friend outside; decide to grab lunch on pier behind Ferry Building. Discuss anterograde amnesia and dating habits of mutual friends. Chicken and tofu cake is delicious. Sun is out, temperature is mild; perfect day to not attend poster sessions.

1:15 – 2 pm. Attend poster session.

2 pm – 5 pm. Presenting poster in 3 hours! Have full-blown panic attack in hotel room. Not about poster, about General Hospital. Why won’t Lulu take Dante’s advice and call support group number for alcoholics’ families?!?! Alcohol is Luke’s problem, Lulu! Call that number!

5 pm. Present world’s most amazing poster to three people. Launch into well-rehearsed speech about importance of work and great glory of sophisticated technical methodology before realizing two out of three people are mistakenly there for coffee and cake, and third person mistook presenter for someone famous. Pause to allow audience to mumble excuses and run to coffee bar. When coast is clear, resume glaring at anyone who dares to traverse poster aisle. Believe strongly in marking one’s territory.

8 pm. Lab dinner at House of Nanking. Food is excellent, despite unreasonably low tablespace-to-floorspace ratio. Conversation revolves around fainting goats, ‘relaxation’ in Thailand, and, occasionally, science.

10 pm. Karaoke at The Mint. Compare performance of CNS attendees with control group of regulars; establish presence of robust negative correlation between years of education and singing ability. Completely wreck voice performing whitest rendition ever of Shaggy’s “Oh Carolina”. Crowd jeers. No, wait, crowd gyrates. In wholesome scientific manner. Crowd is composed entirely of people with low self-monitoring skills; what luck! DJ grimaces through entire song and most of previous and subsequent songs.

2 am. Take cab back to hotel with graduate students and Memory Professor. Memory Professor is drunk; manages to nearly fall out of cab while cab in motion. In-cab conversation revolves around merits of dynamic programming languages. No consensus reached, but civility maintained. Arrival at hotel: all cab inhabitants below professorial rank immediately slip out of cab and head for elevators, leaving Memory Professor to settle bill. In elevator, Graduate Student A suggests that attempt to push Memory Professor out of moving cab was bad idea in view of Graduate Student A’s impending post-doc with Memory Professor. Acknowledge probable wisdom of Graduate Student A’s observation while simultaneously resolving to not adjust own degenerate behavior in the slightest.

2:15 am. Drink at least 24 ounces of water before attaining horizontal position. Fall asleep humming bars of Elliott Smith’s Angeles. Wrong city, but close enough.

Monday, April 4

8 am. Wake up hangover free again! For real this time. No Rocky Steps dance. Shower and brush teeth. Delicately stroke roommate’s cheek (he’ll never know) before heading downstairs for poster session.

8:30 am. Bagels, muffin, coffee. Not necessarily in that order.

9 am – 12 pm. Skip sessions, spend morning in hotel room working. While trying to write next section of grant proposal, experience strange sensation of time looping back on itself, like a snake eating its own tail, but also eating grant proposal at same time. Awake from unexpected nap with ‘Innovation’ section in mouth.

12:30 pm. Skip lunch; for some reason, not very hungry.

1 pm. Visit poster with screaming purple title saying “COME HERE FOR FREE CHOCOLATE.” Am impressed with poster title and poster, but disappointed by free chocolate selection: Dove eggs and purple Hershey’s kisses–worst chocolate in the world! Resolve to show annoyance by disrupting presenter’s attempts to maintain conversation with audience. Quickly knocked out by chocolate eggs thrown by presenter.

5 pm. Wake up in hotel room with headache and no recollection of day’s events. Virus or hangover? Unclear. For some reason, hair smells like chocolate.

7:30 pm. Dinner at Ferry Building with Brain Camp friends. Have now visited Ferry Building at least one hundred times in seventy-two hours. Am now compulsively visiting Ferry Building every fifteen minutes just to feel normal.

9:30 pm. Party at Americano Restaurant & Bar for Young Investigator Award winner. Award comes with $500 and strict instructions to be spent on drinks for total strangers. Strange tradition, but noone complains.

11 pm. Bar is crowded with neuroscientists having great time at Young Investigator’s expense.

11:15 pm. Drink budget runs out.

11:17 pm. Neuroscientists mysteriously vanish.

1 am. Stroll through San Francisco streets in search of drink. Three false alarms, but finally arrive at open pub 10 minutes before last call. Have extended debate with friend over whether hotel room can be called ‘home’. Am decidedly in No camp; ‘home’ is for long-standing attachments, not 4-day hotel hobo runs.

2 am. Walk home.

Tuesday, April 5

9:05 am. Show up 5 minutes late for bagels and muffins. All gone! Experience Apocalypse Now moment on inside, but manage not to show it–except for lone tear. Drown sorrows in Tazo Wild Sweet Orange tea. Tea completely fails to live up to name; experience second, smaller, Apocalypse Now moment. Roommate walks over and asks if everything okay, then gently strokes cheek and brushes away lone tear (he knew!!!).

9:10 – 1 pm. Intermittently visit poster and symposium halls. Not sure why. Must be force of habit learning system.

1:30 pm. Lunch with friends at Thai restaurant near Golden Gate Park. Fill belly up with coconut, noodles, and crab. About to get on table to express gratitude with belly dance, but notice that friends have suddenly disappeared.

2 – 5 pm. Roam around Golden Gate Park and Haight-Ashbury. Stop at Whole Foods for friend to use bathroom. Get chased out of Whole Foods for using bathroom without permission. Very exciting; first time feeling alive on entire trip! Continue down Haight. Discuss socks, ice cream addiction (no such thing), and funding situation in Europe. Turns out it sucks there too.

5:15 pm. Take BART to airport with lab members. Watch San Francisco recede behind train. Sink into slightly melancholic state, but recognize change of scenery is for the best: constitution couldn’t handle more Rocky Steps mornings.

7:55 pm. Suddenly rediscover pronouns as airplane peels away from gate.

8 pm PST – 11:20 MST. The flight’s almost completely empty; I get to stretch out across the entire emergency exit aisle. The sun goes down as we cross the Sierra Nevada; the last of the ice in my cup melts into water somewhere between Provo and Grand Junction. As we start our descent into Denver, the lights come out in force, and I find myself preemptively bored at the thought of the long shuttle ride home. For a moment, I wish I was back in my room at the Hyatt at 8 am–about to run Rocky Steps around the hotel, or head down to the poster hall to find someone to chat with over a bagel and coffee. For some reason, I still feel like I didn’t get quite enough time to hang out with all the people I wanted to see, despite barely sleeping in 4 days. But then sanity returns, and the thought quickly passes.

what Paul Meehl might say about graduate school admissions

Sanjay Srivastava has an excellent post up today discussing the common belief among many academics (or at least psychologists) that graduate school admission interviews aren’t very predictive of actual success, and should be assigned little or no weight when making admissions decisions:

The argument usually goes something like this: “All the evidence from personnel selection studies says that interviews don’t predict anything. We are wasting people’s time and money by interviewing grad students, and we are possibly making our decisions worse by substituting bad information for good.“

I have been hearing more or less that same thing for years, starting when I was grad school myself. In fact, I have heard it often enough that, not being familiar with the literature myself, I accepted what people were saying at face value. But I finally got curious about what the literature actually says, so I looked it up.

I confess that I must have been drinking from the kool-aid spigot, because until I read Sanjay’s post, I’d long believed something very much like this myself, and for much the same reason. I’d never bothered to actually, you know, look at the data myself. Turns out the evidence and the kool-aid are not compatible:

A little Google Scholaring for terms like “employment interviews“ and “incremental validity“ led me to a bunch of meta-analyses that concluded that in fact interviews can and do provide useful information above and beyond other valid sources of information (like cognitive ability tests, work sample tests, conscientiousness, etc.). One of the most heavily cited is a 1998 Psych Bulletin paper by Schmidt and Hunter (link is a pdf; it’s also discussed in this blog post). Another was this paper by Cortina et al, which makes finer distinctions among different kinds of interviews. The meta-analyses generally seem to agree that (a) interviews correlate with job performance assessments and other criterion measures, (b) interviews aren’t as strong predictors as cognitive ability, (c) but they do provide incremental (non-overlapping) information, and (d) in those meta-analyses that make distinctions between different kinds of interviews, structured interviews are better than unstructured interviews.

This seems entirely reasonable, and I agree with Sanjay that it clearly shows that admissions interviews aren’t useless, at least in an actuarial sense. That said, after thinking about it for a while, I’m not sure these findings really address the central question admissions committees care about. When deciding which candidates to admit as students, the relevant question isn’t really what factors predict success in graduate school?, it’s what factors should the admissions committee attend to when making a decision? These may seem like the same thing, but they’re not. And the reason they’re not is that knowing which factors are predictive of success is no guarantee that faculty are actually going to be able to use that information in an appropriate way. Knowing what predicts performance is only half the story, as it were; you also need to know exactly how to weight different factors appropriately in order to generate an optimal prediction.

In practice, humans turn out to be incredibly bad at predicting outcomes based on multiple factors. An enormous literature on mechanical (or actuarial) prediction, which Sanjay mentions in his post, has repeatedly demonstrated that in many domains, human judgments are consistently and often substantially outperformed by simple regression equations. There are several reasons for this gap, but one of the biggest ones is that people are just shitty at quantitatively integrating multiple continuous variables. When you visit a car dealership, you may very well be aware that your long-term satisfaction with any purchase is likely to depend on some combination of horsepower, handling, gas mileage, seating comfort, number of cupholders, and so on. But the odds that you’ll actually be able to combine that information in an optimal way are essentially nil. Our brains are simply not designed to work that way; you can’t internally compute the value you’d get out of a car using an equation like 1.03*cupholders + 0.021*horsepower + 0.3*mileage. Some of us try to do it that way–e.g., by making very long pro and con lists detailing all the relevant factors we can possibly think of–but it tends not to work out very well (e.g., you total up the numbers and realize, hey, that’s not the answer I wanted! And then you go buy that antique ’68 Cadillac you had your eye on the whole time you were pretending to count cupholders in the Nissan Maxima).

Admissions committees face much the same problem. The trouble lies not so much in determining which factors predict graduate school success (or, for that matter, many other outcomes we care about in daily life), but in determining how to best combine them. Knowing that interview performance incrementally improves predictions is only useful if you can actually trust decision-makers to weight that variable very lightly relative to other more meaningful predictors like GREs and GPAs. And that’s a difficult proposition, because I suspect that admissions discussions rarely go like this:

Faculty Member 1: I think we should accept Candidate X. Her GREs are off the chart, great GPA, already has two publications.
Faculty Member 2: I didn’t like X at all. She didn’t seem very excited to be here.
FM1: Well, that doesn’t matter so much. Unless you really got a strong feeling that she wouldn’t stick it out in the program, it probably won’t make much of a difference, performance-wise.
FM2: Okay, fine, we’ll accept her.

And more often go like this:

FM1: Let’s take Candidate X. Her GREs are off the chart, great GPA, already has two publications.
FM2: I didn’t like X at all. She didn’t seem very excited to be here.
FM1: Oh, you thought so too? That’s kind of how I felt too, but I didn’t want to say anything.
FM2: Okay, we won’t accept X. We have plenty of other good candidates with numbers that are nearly as good and who seemed more pleasant.

Admittedly, I don’t have any direct evidence to back up this conjecture. Except that I think it would be pretty remarkable if academic faculty departed from experts in pretty much every other domain that’s been tested (clinical practice, medical diagnosis, criminal recidivism, etc.) and were actually able to do as well (or even close to as well) as a simple regression equation. For what it’s worth, in many of the studies of mechanical prediction, the human experts are explicitly given all of the information passed to the prediction equation, and still do relatively poorly. In other words, you can hand a clinical psychologist a folder full of quantitative information about a patient, tell them to weight it however they want, and even the best clinicians are still going to be outperformed by a mechanical prediction (if you doubt this to be true, I second Sanjay in directing you to Paul Meehl’s seminal body of work–truly some of the most important and elegant work ever done in psychology, and if you haven’t read it, you’re missing out). And in some sense, faculty members aren’t really even experts about admissions, since they only do it once a year. So I’m pretty skeptical that admissions committees actually manage to weight their firsthand personal experience with candidates appropriately when making their final decisions. It seems much more likely that any personality impressions they come away with will just tend to drown out prior assessments based on (relatively) objective data.

That all said, I couldn’t agree more with Sanjay’s ultimate conclusion, so I’ll just end with this quote:

That, of course, is a testable question. So if you are an evidence-based curmudgeon, you should probably want some relevant data. I was not able to find any studies that specifically addressed the importance of rapport and interest-matching as predictors of later performance in a doctoral program. (Indeed, validity studies of graduate admissions are few and far between, and the ones I could find were mostly for medical school and MBA programs, which are very different from research-oriented Ph.D. programs.) It would be worth doing such studies, but not easy.

Oh, except that I do want to add that I really like the phrase “evidence-based curmudgeon“, and I’m totally stealing it.

some people are irritable, but everyone likes to visit museums: what personality inventories tell us about how we’re all just like one another

I’ve recently started recruiting participants for online experiments via Mechanical Turk. In the past I’ve always either relied on on directory listings (like this one) or targeted specific populations (e.g., bloggers and twitterers) via email solicitation. But recently I’ve started running a very large-sample decision-making study (it’s here, if you care to contribute to the sample), and waiting for participants to trickle in via directories isn’t cutting it. So I’ve started paying people (very) small amounts of money for participation.

One challenge I’ve had to deal with is figuring out how to filter out participants who aren’t really interested in contributing to science, and are strictly in it for the money. 20 or 30 cents is a pittance to most people in the developed world, but as I’ve found out the hard way, gaming MTurk appears to be a thriving business in some developing countries (some of which I’ve unfortunately had to resort to banning entirely). Cheaters aren’t so much of an issue for very quick tasks like providing individual ratings of faces, because (a) the time it takes to give a fake rating isn’t substantially greater than giving one’s actual opinion, and (b) the standards for what counts as accurate performance are clear, so it’s easy to train workers and weed out the bad apples. Unfortunately, my studies generally involve fairly long personality questionnaires combined with other cognitive tasks (e.g., in the current study, you get to repeatedly allocate hypothetical money between yourself and a computer partner, and rate some faces). They often take around half an hour, and involve 20+ questions per screen, so there’s a pretty big incentive for workers who are only in it for the cash to produce random responses and try to increase their effective wage. And the obvious question then is how to detect cheating in the data.

One of the techniques I’ve found works surprisingly well is to simply compare each person’s pattern of responses across items with the mean for the entire sample. In other words, you just compute the correlation between each individual’s item scores and the means for all the items scores across everyone who’s filled out the same measure. I know that there’s an entire literature on this stuff full of much more sophisticated ways to detect random responding, but I find this crude approach really does quite well (I’ve verified this by comparing it with a bunch of other similar metrics), and has the benefit of being trivial to implement.

Anyway, one of the things that surprised me when I first computed these correlations is just how strong the relationship between the sample mean and most individuals’ responses is. Here’s what the distribution looks like for one particular inventory, the 181-item Analog to Multiple Broadband Inventories (AMBI, whichI introduced in this paper, and discuss further here):

This is based on a sample of about 600 internet respondents, which actually turns out to be pretty representative of the broader population, as Sam Gosling, Simine Vazire, and Sanjay Srivastava will tell you (for what it’s worth, I’ve done the exact same analysis on a similar-sized off-line dataset from Lew Goldberg’s Eugene-Springfield Community Sample (check out that URL!) and obtained essentially the same results). In this sample, the median correlation is .48; so, in effect, you can predict a quarter of the variance in a typical participant’s responses without knowing anything at all about them. Human beings, it turns out, have some things in common with one another (who knew?). What you think you’re like is probably not very dissimilar to what I think I’m like. Which is kind of surprising, considering you’re a well-adjusted, friendly human being, and I’m a real freakshow somewhat eccentric, paranoid kind of guy.

What drives that similarity? Much of it probably has to do with social desirability–i.e., many of the AMBI items (and those on virtually all personality inventories) are evaluatively positive or negative statements that most people are inclined to strongly agree or disagree with. But it seems to be a particular kind of social desirability–one that has to do with openness to new experiences, and particular intellectual ones. For instance, here are the top 10 most endorsed items (based on mean likert scores across the entire sample; scores are in parentheses):

  1. like to read (4.62)
  2. like to visit new places (4.39)
  3. was a better than average student when I was in school (4.28)
  4. am a good listener (4.25)
  5. would love to explore strange places (4.22)
  6. am concerned about others (4.2)
  7. am open to new experiences (4.18)
  8. amuse my friends (4.16)
  9. love excitement (4.08)
  10. spend a lot of time reading (4.07)

And conversely, here are the 10 least-endorsed items:

  1. was a slow learner in school (1.52)
  2. don’t think that laws apply to me (1.8)
  3. do not like to visit museums (1.83)
  4. have difficulty imagining things (1.84)
  5. have no special urge to do something original (1.87)
  6. do not like art (1.95)
  7. feel little concern for others (1.97)
  8. don’t try to figure myself out (2.01)
  9. break my promises (2.01)
  10. make enemies (2.06)

You can see a clear evaluative component in both lists: almost everyone believes that they’re concerned about others and thinks that they’re smarter than average. But social desirability and positive illusions aren’t enough to explain these patterns, because there are plenty of other items on the AMBI that have an equally strong evaluative component–for instance, “don’t have much energy”, “cannot imagine lying or cheating”, “see myself as a good leader”, and “am easily annoyed”–yet have mean scores pretty close to the midpoint (in fact, the item ‘am easily annoyed’ is endorsed more highly than 107 of the 181 items!). So it isn’t just that we like to think and say nice things about ourselves; we’re willing to concede that we have some bad traits, but maybe not the ones that have to do with disliking cultural and intellectual experiences. I don’t have much of an idea as to why that might be, but it does introspectively feel to me like there’s more of a stigma about, say, not liking to visit new places or experience new things than admitting that you’re kind of an irritable person. Or maybe it’s just that many of the openness items can be interpreted more broadly than the other evaluative items–e.g., there are lots of different art forms, so almost everyone can endorse a generic “I like art” statement. I don’t really know.

Anyway, there’s nothing the least bit profound about any of this; if anything, it’s just a nice reminder that most of us are not really very good at evaluating where we stand in relation to other people, at least for many traits (for more on that, go read Simine Vazire’s work). The nominal midpoint on most personality scales is usually quite far from the actual median in the general population. This is a pretty big challenge for personality psychology, and if we could figure out how to get people to rank themselves more accurately relative to other people on self-report measures, that would be a pretty huge advance. But it seems quite likely that you just can’t do it, because people simply may not have introspective access to that kind of information.

Fortunately for our ability to measure individual differences in personality, there are plenty of items that do show considerable variance across individuals (actually, in fairness, even items with relatively low variance like the ones above can be highly discriminative if used properly–that’s what item response theory is for). Just for kicks, here are the 10 AMBI items with the largest standard deviations (in parentheses):

  1. disliked math in school (1.56)
  2. wanted to run away from home when I was a child (1.56)
  3. believe in a universal power or god (1.53)
  4. have felt contact with a divine power (1.51)
  5. rarely cry during sad movies (1.46)
  6. am able to fix electrical-wiring problems (1.46)
  7. am devoted to religion (1.44)
  8. shout or scream when I’m angry (1.43)
  9. love large parties (1.42)
  10. felt close to my parents when I was a child (1.42)

So now finally we come to the real moral of this post… that which you’ve read all this long way for. And the moral is this, grasshopper: if you want to successfully pick a fight at a large party, all you need to do is angrily yell at everyone that God told you math sucks.

to each their own addiction

An only slightly fictionalized story, for my long-suffering wife.

“It’s happening again,” I tell my wife from the couch. “I’m having that soul-crushing experience again.”

“Too much work?” she asks, expecting the answer to be yes, since no matter what quantity of work I’m actually burdened with at any given moment, the way I describe it to to other people when they ask is always “too much.”

“No,” I say. “Work is fine right now.”

“Had a paper rejected?”

“Pfft, no,” I say. “Like that ever happens to me!” (I don’t tell her it’s happened to me twice in the past week.)

“Then what?”

“The blog posts,” I tell her, motioning to my laptop screen. “There’s just too many of them in my Reader. I can’t keep up! I’m drowning in RSS feeds!”

My wife has learned not to believe anything I say, ever; we’ve lived together long enough that her modal response to my complaints is an arched eyebrow. So I flip my laptop around and point at the gigantic bolded text in the corner that says All Items (118). Emotionally gigantic, I mean; physically, I think it’s only like 12 point font.

“One hundred and eighteen blog posts!” I yell at absolutely no one. “I’m going to be here all night!”

“That’s because you live here,” she helpfully points out.

I’m not sure exactly when I became enslaved by my blog feeds. I know it was sometime after Carl Zimmer‘s amazing post about the man-eating fireflies of Sri Lanka, and sometime before the Neuroskeptic self-published his momentous report introducing three entirely new mental health diagnoses. But that’s as much as I can tell you; the rest is lost in a haze of rapid-scrolling text, retweeted links, and never-ending comment threads. There’s no alarm bell that sounds out loud to indicate that you’ve stomped all over the line that separates occasional indulgence from outright “I can quit any time, honest!” abuse. No one shows up at your door, hands you a bucket of Skittles, and says, “congratulations! You’re hooked on feeds!”

The thought of all those unread posts piling up causes me to hyperventilate. My wife, who sits unperturbed in her chair as 1,000+ unread articles pile up in her Reader, stares at me with a mixture of bemusement and horror.

“Let’s go for a walk,” she suggests, making a completely transparent effort to distract me from my immense problems.

Going for a walk is, of course, completely out of the question; I still have 118 blog posts to read before I can do anything else. So I read all 118 posts, which turns out not to take all night, but more like 15 minutes (I have a very loose definition of reading; it’s closer to what other people call ‘seeing’). By the time I’ve done that, the internet has written another 8 new articles, so now I feel compelled to read those too. So I do that, and then I hit refresh again, and lo and behold, there are 2 MORE articles. So I grudgingly read those as well, and then I quickly shut my laptop so that no new blog posts can sneak up on me while I’m off hanging out in Microsoft Word pretending to do work.

Screw this, I think after a few seconds, and run to find my wife.

“Come on, let’s go for that walk,” I say, running as fast as I can towards my sandals.

“What’s the big rush,” she asks. “I want to go walking, not jogging; I already went to the gym today.”

“No choice,” I say. “We have to get back before the posts pile up again.”

“What?”

“I said, I have a lot of work to do.”

So we go out walking, and it’s nice and all that; the temperature is probably around 70 degrees; it’s cool and dry and the sun’s just going down; the ice cream carts are out in force on the Pearl Street mall; the jugglers juggle and the fire eaters eat fire and give themselves cancer; a little kid falls down and skins his knee but gets up and laughs like it didn’t even hurt, which it probably didn’t, because everyone knows children under seven years of age don’t have a central nervous system and can’t feel pain. It’s a really nice walk, and I’m happy we’re on it, but the whole time I keep thinking, How many dozens of posts has PZ Myers put up while I’ve been gone? Are Razib Khan and Ed Yong posting their link dumps as I think this? And what’s the over-under on the number of posts in my ‘cog blogs’ folder?

She sees me doing all this of course, and she’s not happy about it. So she lets me know it.

“I’m not happy about this,” she says.

When we get back, we each back to our respective computer screen. I’m relieved to note that the internet’s only made 11 more deliveries, which I promptly review and discharge. I star two posts for later re-consideration and let the rest disappear into the ether of spent words. Then I open up a manuscript I’ve been working on for a while and pretend to do some real work for a couple of hours. With periodic edutainment breaks, of course.

Around 11:30 pm I decide to close up shop for the night. No one really blogs after about 9 pm, which is fortunate, or I’d never get any sleep. It’s also the reason I avoid subscribing to European blogs if I can help it. Europeans have no respect for Mountain Time.

“Are you coming to bed,” I ask my wife.

“Not yet,” she says, looking guilty and avoiding eye contact.

“Why not? You have work to do?”

“Nope, no work.”

“Cooking? Are you making a fancy meal for dinner tomorrow?”

“No, it’s your turn to cook tomorrow,” she says, knowing full well that my idea of cooking consists of a take-out menu and telephone.

“Then what?”

She opens her mouth, but nothing comes out. The words are all jammed tightly in between her vocal cords.

Then I see it, poking out on the couch from under a pillow: green cover, 9 by 6 inches, 300 pages long. It’s that damn book!

“You’re reading Pride and Prejudice again,” I say. It’s an observation, not a question.

“No I’m not.”

“Yes you are. You’re reading that damn book again. I know it. I can see it. It’s right there.” I point at it, just so that there can’t possibly be any ambiguity about which book I’m talking about.

She gazes around innocently, looking at everything but the book.

“What is that, like the fourteenth time this year you’ve read it?”

“Twelfth,” she says, looking guilty. “But really, go to bed without me; I might be up for a while still. I have another fifty pages or so I need to finish before I can go to sleep. I just have to find out if Elizabeth Bennet and Mr. Darcy end up together.”

I look at her mournfully, quietly shut my laptop’s lid, and bid the both of them–wife and laptop–good night. My wife grudgingly nods, but doesn’t look away from Jane Austen’s pages. My RSS feeds don’t say anything either.

“Yes,” I mumble to no one in particular, as I slowly climb up the stairs and head for my toothbrush.

“Yes, they do end up together.”

you can’t make this stuff up (but Freud could)

Out of idle curiosity, I just spent a few minutes looking up the origin of the phrase “the narcissism of small differences.” Turns out it’s one of Freud’s many contributions to our lexicon, and originates in his 1917 article The Taboo of Virginity:

Crawley, in terms that are hardly distinguishable from those employed by psychoanalysis, sets forth how each individual is separated from the others by a “taboo of personal isolation” and that it is precisely the little dissimilarities in persons who are otherwise alike that arouse feelings of strangeness and enmity between them. It would be tempting to follow up this idea and trace back to this “narcissism of small differences” the antagonism which in all human relations we see successfully combating feelings of fellowship and the commandment of love towards all men.

…so there’s that question answered. As Freud goes, this is positively lucid prose; for context, the very next sentence is: Psychoanalysis believes that, in pointing out the castration complex and its influence on the estimation in which women are held, it has discovered one of the chief factors underlying the narcissistic rejection of women by men that is so liberally mingled with disdain.

And then there are lots of other little gems in the same article, like this one:

We know, however, that the first act of intercourse is by no means always followed by this behaviour; very often the experience merely signifies a disappointment to the woman, who remains cold and unsatisfied; usually it takes some time and frequent repetition of the sexual act before satisfaction in it for her too sets in.

Freud justifiably gets a lot of credit for revolutionizing the study of the mind, but it’s worth remembering that he also did a lot of cocaine.

repost: narrative tips from a grad school applicant

Since it’s grad school application season for undergraduates, I thought I’d repost some narrative tips about how to go about writing a personal statement for graduate programs in psychology. This is an old, old post from a long-deceased blog; it’s from way back in 2002 when I was applying to grad school. It’s kind of a serious piece; if I were to rewrite it today, the tone would be substantially lighter. I can’t guarantee that following these tips will get you into grad school, but I can promise that you’ll be amazed at the results.

The first draft of my personal statement was an effortful attempt to succinctly sum up my motivation for attending graduate school. I wanted to make my rationale for applying absolutely clear, so I slaved over the statement for three or four days, stopping only for the occasional bite of food and hour or two of sleep every night. I was pretty pleased with the result. For a first draft, I thought it showed great promise. Here’s how it started:

I want to go to,o grajit skool cuz my frend steve is in grajit and he says its ez and im good at ez stuff

When I showed this to my advisor he said, “I don’t know if humor is the way to go for this thing.“

I said, “What do you mean, humor?“

After that I took a three month break from writing my personal statement while I completed a grade 12 English equivalency exam and read a few of the classics to build up my vocabulary. My advisor said that even clever people like me needed help sometimes. I read Ulysses, The Odyssey, and a few other Greek sounding books, and a book called The Cat in the Hat which was by the same author as the others, but published posthumously. Satisfied that I was able to write a letter that would impress every graduate admissions committee in the world, I set about writing a second version of my personal statement. Here’s how that went:

Dear Dirty Admissions Committee,
Solemn I came forward and mounted the round gunrest. I faced about and blessed gravely thrice the Ivory Tower, the surrounding country, and all the Profs. Then catching sight of the fMRI machine, I bent towards it and made rapid crosses in the air, gurgling in my throat and shaking my head.

“Too literary,“ said my advisor when I showed him.

“Mud,“ I said, and went back to the drawing board.

The third effort was much better. I had weaned myself off the classics and resolved to write a personal statement that fully expressed what a unique human being I was and why I would be an asset to the program. I talked about how I could juggle three bean bags and almost four, I was working on four, and how I’d stopped biting my fingernails last year so I had lots of free time to do psychology now. To show that I was good at following through on things that I started, I said,

p.s. when I can juggle four bean bags ( any day now) I will write you to let you know so you can update your file.

Satisfied that I had written the final copy of my statement, I showed it to my advisor. He was wild-eyed about it.

“You just don’t get it, do you,“ he said, ripping my statement in two and throwing it into the wastepaper basket. “Tell you what. Why don’t I write a statement for you. And then you can go through it and make small changes to personalize it. Ok?“

“Sure,“ I said. So the next day my advisor gave me a two-page personal statement he had written for me. Now I won’t bore you with all of the details, but I have to say, it was pretty bad. Here’s how it started:

After studying psychology for nearly four years at the undergraduate level, I have decided to pursue a Ph.D. in the field. I have developed a keen interest in [list your areas of interest here] and believe [university name here] will offer me outstanding opportunities.

“Now go make minor changes,“ said my advisor.

“Mud,“ I said, and went to make minor changes.

I came back with the final version a week later. It was truly a masterpiece; co-operating with my advisor had really helped. At first I had been skeptical because what he wrote was so bad the way he gave it to me, but with a judicious sprinkling of helpful clarifications, it turned into something really good. It was sort of like an ugly cocoon (his draft) bursting into a beautiful rainbow (my version). It went like this:

After studying psychology (and juggling!) for nearly four years at the undergraduate level (of university), I have decided to pursue a Ph.D. in the field. Cause I need it to become a Prof. I have developed a keen interest in [list your areas of interest here Vision, Language, Memory, Brain] and believe [university name hereStanford Princeton Mishigan] will offer me outstanding opportunities in psychology and for the juggling society.

“Brilliant,“ said my advisor when I showed it to him. “You’ve truly outdone yourself.“

“Mud,“ I said, and went to print six more copies.

just a quick note to say…

…I’m not dead, just applying for jobs and trying to get some papers out of the door. Regular posting (meaning, weekly, as opposed to monthly) will resume soon! Until then, go read something interesting. Like this, or this, or this, or this, or this, or this.

Okay, none of those ‘this’es actually link to anything. I was going to do a quick link dump, and then realized that in my current fatigued state, digging up six interesting links would be an epic undertaking. Like, elephant-lifting epic. So no links today. But I promise I’ll make up for it when I’m less tired. We’ll go to Disney World, eat ice cream, and gossip about what all the other science bloggers are wearing. There will be blood posts!

PLoS ONE needs new subjects

I like the PLoS journals, including PLoS ONE, a lot. But it drives me a little bit crazy that the list of PLoS ONE subjects includes things like Non-Clinical Health, Nutrition, and Science Policy, while perfectly respectable subjects like Psychology, Economics, and Political Science are nowhere to be found (note: I’m not saying there’s anything wrong with Nutrition, just that there’s also nothing wrong with Psychology).

I can sort of understand the rationale; PLoS ONE is supposed to be a science journal, and I imagine the editors feel that if they opened up the door to the aforementioned categories, some of the submissions they’d start receiving would have tenuous or nonexistent relationships to anything that you could call science. But in practice, PLoS ONE already does take articles in all of those subjects–and many others. And what then happens, no doubt, is that the editorial board has epic battles over which of the 40-odd existing subjects is going to become the proud beneficiary of a completely unrelated article.

I imagine it goes down something like this:

Editor A: Look, “Patriarchal principles of pop music in a post-Jacksonian era” is clearly an Epidemiology article. It’s going under Public Health and Epidemiology.

Editor B: Don’t be a fool. There isn’t a single word in the paper about health or disease. You’d know that if you’d bothered to read it. It obviously belongs under Mental Health.

Editor A: Absolutely not. Infectious Diseases, Pediatrics and Child Health, or Anesthesiology and Pain Management. Pick one. Final offer.

Editor B: No. But I’ll tell you what. Send it back to the authors, ask them to add a section on the influence of barbiturates and opiates on modern composition, and then we’ll stick it under Pharmacology.

Editor A: Deal.

Lest you think I’m making shit up exaggerating, witness exhibit A: a paper published today by Araújo et al entitled “Tactical Voting in Plurality Elections”. To be fair, I don’t know anything about tactics, voting, plurality, or elections, so I can’t tell you if the paper is any good or not. It looks interesting, but I don’t understand much more than the abstract.

What I can tell you though with something approaching certainty is that the paper has absolutely nothing to do with Neuroscience–which is one of the categories it’s filed under (the other is Physics, which it also seems to bear no relation to, save for the fact that the authors are physicists). It doesn’t mention the words ‘brain’, ‘neuro-‘, ‘neural’, or ‘neuron’ anywhere in the text, which is pretty much a necessary condition for a neuroscience article in my book. The only conceivable link I can think of is that it’s a paper about voting, and voting is done by people, and people have brains. But that’s not very compelling. Really, it should go under Political Science, or Economics, or Applied Statistics, or even a catch-all category like Social Sciences. Except that none of those exist.

Pretty please, PLoS ONE, can we get a Social Sciences section?