Monthly Archives: March 2014

life after bem – Simine Vazire (sometimes i'm wrong)

Bear_longing

many people have written about how bem's esp paper was one of the major factors that triggered the latest scientific integrity movement in social/personality psychology.  that is an interesting story.  but that is not the bem paper i want to talk about today.

i have come here today to discuss bem's chapter, 'writing the empirical journal article' (2003) that i - and i suspect many others - used to assign to every undergrad and graduate student taking our psychology research methods classes.  there are many extremely wise points in that chapter.  but there are also many pieces of advice that seem entirely antiquated today.  if the bem chapter is no longer the gold standard for how to write an empirical article, what is? (see also: laura king's article for the spsp dialogue (pdf, p. 6)).

i was reminded of the complexity of this question when a historian friend of mine suggested i read 'the question of narrative in contemporary historical theory' by hayden white (1984). i will share a few quotes with you:

'but it is precisely because the narrative mode of representation is so natural to human consciousness, so much an aspect of everyday speech and ordinary discourse, that its use in any field of study aspiring to the status of a science must be suspect. for whatever else a science may be, it is also a practice which must be as critical about the way it describes its objects of study as it is about the way it explains their structures and processes.'

'a discipline that produces narrative accounts of its subject matter as an end in itself seems methodologically unsound; one that investigates its data in the interest of telling a story about them appears theoretically deficient. Continue reading

Things that make me skeptical… – Brent Donnellan (The Trait-State Continuum)

Simine Vazire crafted a thought provoking blog post about how some in the field respond to counter-intuitive findings.  One common reaction among critics of this kind of research is to claim that the results are unbelievable.   This reaction seems to fit with the maxim that extraordinary claims should require extraordinary evidence (AKA the Sagan doctrine).  For example, the standard of evidence needed to support the claim that a high-calorie/low nutrient diet coupled with a sedentary life style is negatively associated with morbidity might be different than the standard of proof needed to support the claim that attending class is positively associated with exam performance.  One claim seems far more extraordinary than the other.  Put another way: Prior subjective beliefs about the truthiness of these claims might differ and thus the research evidence needed to modify these pre-existing beliefs should be different.

I like the Sagan doctrine but I think we can all appreciate the difficulties that arise when trying to determine standards of evidence needed to justify a particular research claim.  There are no easy answers except for the tried and true response that all scientific claims should be thoroughly evaluated by multiple teams using strong methods and multiple operational definitions of the underlying constructs.  But this is a “long term” perspective and provides little guidance when trying to interpret any single study or package of studies.  Except that it does, sort of.  A long term perspective means that most findings should be viewed with a big grain of salt, at least initially.  Skepticism is a virtue (and I think this is one of the overarching themes of Simine’s blog posts thus far).   However, skepticism does not preclude publication and even some initial excitement about an idea.  It simply precludes making bold and definitive statements based on initial results with unknown generality. Continue reading

What is counterintuitive? – Sanjay Srivastava (The Hardest Science)

Simine Vazire has a great post contemplating how we should evaluate counterintuitive claims. For me that brings up the question: what do we mean when we say something is “counterintuitive?”

First, let me say what I think counterintuitive isn’t. The “intuitive” part points to the fact that when we label something counterintuitive, we are usually not talking about contradicting a formal, well-specified theory. For example, you probably wouldn’t say that the double-slit experiment was “counterintuitive;” you’d say it falsified classical mechanics.

In any science, though, you have areas of inquiry where there is not an existing theory that makes precise predictions. In social and personality psychology that is the majority of what we are studying. (But it’s true in other sciences too, probably more than we appreciate.) Beyond the reach of formal theory, scientists develop educated guesses, hunches, and speculations based on their knowledge and experience. So the “intuitive” in counterintuitive could refer to the intuitions of experts.

But in social and personality psychology we study phenomena that regular people reflect on and speculate about too. A connection to everyday lived experience is almost definitional to our field, whether you think it is something that we should actively pursue or just inevitably creeps in. Continue reading

What did Malcolm Gladwell actually say about the 10,000 hour rule? – Sanjay Srivastava (The Hardest Science)

A new paper out in Intelligence, from a group of authors led by David Hambrick, is getting a lot of press coverage for having “debunked” the 10,000-hour rule discussed in Malcolm Gladwell’s book Outliers. The 10,000-hour rule is — well, actually, that’s the point of this post: Just what, exactly, is the 10,000-hour rule?

The debate in Intelligence is between Hambrick et al. and researcher K. Anders Ericsson, who studies deliberate practice and expert performance (and wrote a rejoinder to Hambrick et al. in the journal). But Malcolm Gladwell interpreted Ericsson’s work in a popular book and popularized the phrase “the 10,000-hour rule.” And most of the press coverage mentions Gladwell.

Moreover, Gladwell has been the subject of a lot of discussion lately about how he interprets research and presents his conclusions. The 10,000-hour rule has become a runaway meme — there’s even a Macklemore song about it. And if you google it, you’ll find a lot of people talking about it and trying to apply it to their lives. The interpretations aren’t always the same, suggesting there’s been some interpretive drift in what people think the 10,000-hour rule really is. I read Outliers shortly after it came out, but my memory of it has probably been shaped by all of that conversation that has happened since. Continue reading

unbelievable. – Simine Vazire (sometimes i'm wrong)


Escher2


one of the most fascinating dimensions along which psychology researchers differ is in their reaction to counterintuitive findings.  when some people say 'i can't believe it!' they mean it as a compliment.  when others say it, you should take cover.  how should we feel about counterintuitive findings?

i'll come out and say it: i have not drunk the bayesian kool-aid. i do like the idea that the amount of evidence required to support a claim should depend on the plausibility of that claim to begin with, but the reason i'm not a whole-hearted bayesian is that i am skeptical that there will be much consensus in psychology about which claims are more or less probable.  (have you ever asked a group of psychologists what proportion of our a priori hypotheses are likely to be right? you should try it, it's a fun party trick.) but i have seen cases where pretty much everyone agrees that a conclusion is very counterintuitive (in fact, there are quite a few cases where the authors themselves appeal to this as a selling point of their work).  and in those cases we can ask: given that we all agree this is surprising, should we hold the research to a higher standard? do the authors need more evidence if the claim they are making is widely acknowledged to be shocking?

Continue reading

is bad replication a sin? – Simine Vazire (sometimes i'm wrong)

 

should replications be held to a higher standard than original research?

i have seen some very bright and influential people argue that they should, mainly because of the potential damage that a failed replication could do to the original author's reputation.  according to this argument, shoddy original research may be 'irresponsible' but shoddy replication is a 'sin'.* 

i have several objections to this.

1. original research is often treated as precedent.  my impression is that people see the original finding as very likely to be true, and require a lot of new evidence to be convinced otherwise.  this is problematic for many reasons, but if it's true, it's all the more reason to hold original research to a very high standard.  giving original research a pass is dangerous given how hard it is to overturn a finding once it is in the literature.

2. Continue reading

i always live without knowing – Simine Vazire (sometimes i'm wrong)

Feynman3

 

magical things can still happen in used bookstores.

i was killing time in one and came across a book by richard feynman called 'the meaning of it all'.  i noticed that the first essay was called 'the uncertainty of science'. i bought it.  it was the best $4 i've spent in a while.

it is tempting to just re-type the entire essay here, but in the interest of trying not to violate copyright, and trying to contribute something of my own, i will share some excerpts and reflections.

first, feynman on p-hacking:

'it is necessary to look at the results of observation objectively, because you, the experimenter, might like one result better than another. you perform the experiment several times, and because of irregularities, like pieces of dirt falling in, the result varies from time to time. you do not have everything under control. Continue reading

I’m Using the New Statistics – Michael Kraus (Psych Your Mind)

Do you remember your elementary school science project? Mine was about ant poison. I mixed borax with sugar and put that mixture outside our house during the summer in a carefully crafted/aesthetically pleasing "ant motel." My prediction, I think, was that we would kill ants just like in the conventional ant killing brands, but we'd do so in an aesthetically pleasing way. In retrospect, not sure I was cut out for science back then.

Anyway, from what I remember about that process, there was a clear study design and articulation of a hypothesis--a prediction about what I expected to happen in the experiment. Years later, I would learn more about hypothesis testing in undergraduate and graduate statistical courses on my way to a social psychology PhD. For that degree, Null Hypothesis Significance Testing (NHST) would be my go-to method of inferential statistics.

In NHST, I have come to an unhealthy worship of p-values--the statistic expressing the probability of the data showing the observed relationship between variables X and Y, if the null hypothesis (of no relationship) were true. If p < .05 rejoice! If p < .10 claim emerging trends/marginal significance and be cautiously optimistic. If p > .10 find another profession. Continue reading

strong opinions about data sharing mandates–mine included – Tal Yarkoni ([citation needed])

Apparently, many scientists have rather strong feelings about data sharing mandates. In the wake of PLOS’s recent announcement–which says that, effective now, all papers published in PLOS journals must deposit their data in a publicly accessible location–a veritable gaggle of scientists have taken to their blogs to voice their outrage and/or support for the policy. The nays have posts like DrugMonkey’s complaint that the inmates are running the asylum at PLOS (more choice posts are here, here, here, and here); the yays have Edmund Hart telling the nays to get over themselves and share their data (more posts here, here, and here). While I’m a bit late to the party (mostly because I’ve been traveling and otherwise indisposed), I guess I’ll go ahead and throw my hat into the ring in support of data sharing mandates. For a number of reasons outlined below, I think time will show the anti-PLOS folks to very clearly be on the wrong side of this issue.

Mandatory public deposition is like, totally way better than a “share-upon-request” approach

You might think that proactive data deposition has little incremental utility over a philosophy of sharing one’s data upon request, since emails are these wordy little things that only take a few minutes of a data-seeker’s time to write. But it’s not just the time and effort that matter. It’s also the psychology and technology. Psychology, because if you don’t know the person on the other end, or if the data is potentially useful but not essential to you, or if you’re the agreeable sort who doesn’t like to bother other people, it’s very easy to just say, “nah, I’ll just go do something else”. Scientists are busy people. If a dataset is a click away, many people will be happy to download that dataset and play with it who wouldn’t feel comfortable emailing the author to ask for it. Technology, because data that isn’t publicly available is data that isn’t publicly indexed. It’s all well and good to say that if someone really wants a dataset, they can email you to ask for it, but if someone doesn’t know about your dataset in the first place–because it isn’t in the first three pages of Google results–they’re going to have a hard time asking.

Continue reading

The Deathly Hallows of Psychological Science – Brent Roberts (pigee)

By Brent W. Roberts

As of late, psychological science has arguably done more to address the ongoing believability crisis than most other areas of science.  Many notable efforts have been put forward to improve our methods.  From the Open Science Framework (OSF), to changes in journal reporting practices, to new statistics, psychologists are doing more than any other science to rectify practices that allow far too many unbelievable findings to populate our journal pages.

The efforts in psychology to improve the believability of our science can be boiled down to some relatively simple changes.  We need to replace/supplement the typical reporting practices and statistical approaches by:

  1. Providing more information with each paper so others can double-check our work, such as the study materials, hypotheses, data, and syntax (through the OSF or journal reporting practices).
  2. Designing our studies so they have adequate power or precision to evaluate the theories we are purporting to test (i.e., use larger sample sizes).
  3. Providing more information about effect sizes in each report, such as what the effect sizes are for each analysis and their respective confidence intervals. Continue reading