Replication and Reproducibility Event II: Moving Psychological Science Forward

On Friday 26th of January at the Royal Society there was a series of talk on how psychology could progress as a science, with an emphasis on replication and reproducibility. I’m going to summarise the key points from the individual talks and make a few comments. A collection of all the individual videos of the talks can be found here.

Professor Daryl O’Connor – “Psychological Science as a Trailblazer for Science?”

  • The Reproducibility Project (2015) started this movement off.
  • The number of positive developments that arose due to the findings from the Reproducibility Project (2015) e.g. the Centre for Open Science, the Open Science Framework, Registered Reports and their associated format the Registered Replication Report, among other things, is very encouraging.
  • The argument can be made that the field as a whole is improving.
  • The discussion on social media over the Boston globe article is an example of constructive disagreement e.g. between Amy Cuddy and Brian Nosek.
  • But is there some element of researchers forming echo chambers among like-minded peers over the perennial tone debate?
  • Science as a behaviour model. Behaviour occurs as an interaction between three necessary conditions: capability (an individual’s psychological and physical capacity to engage in the activity concerned), motivation (reflective and automatic processes that increase or decrease your desire to engage in the behaviour), and opportunity (all the factors outside the individual which make the behaviour possible or prompt it). These affect and are affected by behaviour.
  • Other fields have taken note of what psychology has done and are learning from us.
  • The “revolutionaries” have improved scientific practice and triggered new ways of working.
  • All levels of science need to be targeted, including methodologies and incentive structures.
  • It is a very exciting time to be a scientist, especially an Early Career Researcher (E.C.R) because of all the changes.


Some people have argued they first started taking notice of the problems in psychology in 2011, with the publication of Simons, Nelson, & Simonsohn (2011) and Bem (2011). Regardless of an individual researchers starting point, the field has made great strides in a short space of time. Of course the calls to action have been ringing out for years, but actual change seems to be occurring which is highly encouraging. And I agree with O’Connor’s point that it has mainly come about because of the actions of those branded as “revolutionaries”. This isn’t to dismiss a genuine discussion about how these criticisms should be handled and that sometimes they can go to far. I think having that debate is important as it keeps the process in check. But progress isn’t going to be painless, though this pain should be minimised. As for social media, I generally think it has been a force for good with increased chances of visibility and interaction for those who typically take a back seat in discussions (though old power structures are still highly relevant and should be challenged). It is also almost universally in favour of measures to improve replicability and methodological rigour so people can see positive examples of these measures and be rewarded via complements. read more

Ability grouping of students doesn’t work

Academic achievement in England is strongly impacted by class, with those of a higher socioeconomic status (S.E.S.) more likely to achieve than than those of a lower S.E.S. (Clifton & Cook, 2012). These gaps between students can be seen between students as early as three years old (Feinstein, 2003) and continue to widen as the children age (Feinstein, 2004). One of the historical measures to reduce these inequalities is ability grouping. Students are placed into groups based on their test scores for certain subjects so they can be taught with their peers of similar ability. ‘Streaming’ (called ‘tracking’ in the US) divides students into groups based on their test scores across all/most of their subjects, meaning they stay with the same students across those subjects. This is similar to ‘banding’. ‘Setting’ occurs when students are put into ability groups for specific subjects that are not necessarily consistent across subjects e.g. a student could be placed in top set for maths but middle set for English (Francis et al., 2017). Data on the prevalence of ability grouping is inconsistent but the evidence suggests it is prevalent in secondary school and to a lesser extent primary school in the U.K. (Dracup, 2014). It is becoming more common in the U.S. after a drop in popularity during the 1990’s (Steenbergen-Hu, Makel, & Olszewski-Kubilius, 2016). read more

Notes on Paul Meehl’s “Philosophical Psychology Session” #07

These are the notes I made whilst watching the video recording of Paul Meehl’s philosophy of science lectures. This is the seventh episode (a list of all the videos can he found here). Please note that these posts are not designed to replace or be used instead of the actual videos (I highly recommend you watch them). They are to be read alongside to help you understand what was said. I also do not include everything that he said (just the main/most complex points).

  • Example for Lyken’s crud factor:

T is literally true, two auxiliary theories (A1 and A2) both of which have a .9 probability of being true, cp clause has a .9 probability of being true, and the conditions have a .9 probability of being true. What’s the probability (given the above) that o1o2? .94=.66. Chances of getting that result because of theory being true is 2/3 even if you had perfect power. With 80% the probability is .52 of the observation coming from the theory. read more

Best reads of 2017

These are some of the best or most thought-provoking articles I’ve read this year. The categories and articles are organised alphabetically and I don’t necessarily agree with the ideas put forward.


Labour’s Higher Education proposals will cost £8bn per year, although increase the deficit by more. Graduates who earn most in future would benefit most by Chris BelfieldJack Britton, and Laura van der Erve. A strong counter argument against free tuition for all university students. read more

Why you should think of statistical power as a curve

Statistical power is defined as “the probability of correctly rejecting H0 when a true association is present” where H0 is the null hypothesis, often an association or effect size of zero (Sham & Purcell, 2014). It is determined by the the effect size you want to detect, the size of your sample (N), and the alpha level which is typically 0.05 but you can set it to whatever you want (Lakens et al. 2017). I always thought of power as a static value for your study.

But this is wrong. read more

Why do people leave academia?- The results

On social media, there are often discussions about why psychologists leave academia. Some argue that the new culture of criticism (where overly harsh criticism is leveled against those who make errors and accusations of malfeasance are rife) make academics, especially younger ones, change profession. They give examples of high profile cases where researchers have made errors or merely used previously accepted standards of practice and the obloquy they’ve received when their results don’t hold up. Others provide counter examples of former colleagues who grew frustrated at their inability to replicate supposedly rock-solid findings or who had a crisis in confidence about the validity of vast swathes of the literature. But one thing is lacking from this discussion. read more

Notes on Paul Meehl’s “Philosophical Psychology Session” #06

These are the notes I made whilst watching the video recording of Paul Meehl’s philosophy of science lectures. This is the sixth episode (a list of all the videos can he found here). Please note that these posts are not designed to replace or be used instead of the actual videos (I highly recommend you watch them). They are to be read alongside to help you understand what was said. I also do not include everything that he said (just the main/most complex points).

A core postulate is one that is found in every derivation chain or a postulate that consists of only core concepts. A core concept is one that is relied on implicitly in every derivation chain is in the hard core. read more

I’m a non-methodologist, does it matter if my definition is slightly wrong?

A few weeks ago, Nature published an article summarising the various measures and counter-measures suggested to improve statistical inferences and science as a whole (Chawla, 2017). It detailed the initial call to lower the significance threshold to 0.005 from 0.05 (Benjamin et al., 2017) and the paper published in response (Lakens et al., 2017). It was a well written article, with one minor mistake: an incorrect definition of a p-value: 

The two best sources for the correct definition of a p-value (along with its implications and examples of how a p-value can be misinterpreted) are Wasserstein & Lazar (2016) and its supplementary paper Greenland et al. (2016). A p-value has been defined as: “a statistical summary of the compatibility between the observed data and what we would predict or expect to see if we knew the entire statistical model (all the assumptions used to compute the P value) were correct” (Greenland et al., 2016).  To put it another way, it tells us the probability of finding the data you have or more extreme data assuming the null hypothesis (along with all the other assumptions about randomness in sampling, treatment, assignment, loss, and missingness, the study protocol, etc.) are true. The definition provided in the Chawla article is incorrect because it states “the smaller the p-value, the less likely it is that the results are due to chance”. This gets things backwards: the p-value is a probability deduced from a set of assumptions e.g. the null hypothesis is true, so it can’t also tell you the probability of that assumption at the same time. Joachim Vandekerckhove and Ken Rothman give further evidence as to why this definition is incorrect: read more

Assessing the validity of labs as teaching methods and controlling for confounds

Anyone who has taken one of the harder sciences at university or knows someone who has will know what “labs” are. You are given practical assignments to complete that are meant to consolidate what you’ve learnt in the lecture/seminar. They are almost ubiquitous in physics after becoming widespread by the beginning of the 20th century (Meltzer & Otero, 2015), as they are for chemistry (Layton, 1990), and biology (Brownell, Kloser, Fukami, & Shavelson, 2012). Their value is widely assumed to have been demonstrated multiple times across the hard sciences (Finkelstein et al., 2005; Blosser, 1990) but questions have occasionally been raised as to their effectiveness (Hofstein & Lunetta, 2004). A new paper by Holmes, Olsen, Thomas, & Wieman (2017) sought to test whether participating in labs actually improved physics students’ final grades or not. Across three American universities they tested three questions: what is the impact of labs on associated exam performance; did labs selectively impact the learning physics concepts; and are there short-term learning benefits that are “washed out on the final exams”? read more

Why do psychologists leave academia?

Every once in a while in the psychology sphere of social media there’s a discussion about why people leave academia. This talking point often comes up in the context of “the open science movement” and whether more academics leave because of the cultural of criticism or because of the lack of replicability of some findings. People who have left academia offer their reasons and people who are still in give several anecdotes about why someone they know left. But what seems to be lacking is some actual data. So I’ve written this survey with the hopes of shedding some light on the situation. It’s for people who have considered leaving or have actually left academia or practicing psychology (educational, clinical, etc.). But this survey will only be useful if you share this with people you know who have left. So please share the survey on social media or relevant mailing lists but especially link it directly to people you know who have left psychology. I’m writing this blog post so those who are subscribed to the methods blog feed will see this survey, hopefully increasing the number of respondents. Thank you for your help. read more