In “Three mild suggestions for Psychology” 13 August I made three suggestions which I summarise below.
1 Agree upon some basic measures. It would be alarming in any other discipline if, after a century of enquiry, we still had no agreement about what psychological measures we should apply as a matter of course.
2 Agree to pay attention to previous research, and relevant research in related fields. Psychology has an alarming tendency to ignore previous work, particularly when terminology changes, which is frequently. It often also ignores problems with measuring techniques, as if it were optional to attend to these matters.
3 Agree to collaborate, and move from sole practitioners in cottage industries to more systematic large scale research projects. Academic advancement is based on “making a name for one’s self” which encourages apprentice piece publications, repetition of papers each dealing with sub-sections of a data set, and anything which brings attention to a person. Imagine if the smallest publishable sample size was 500 persons: might that drive up the representativeness and reproducibility of results?
Earlier, on 18th April, I had made some gentle criticisms in “Not all neuroscience is rubbish, just 92% of it” which concluded: “Next time you see a pretty MRI picture of the brain, look at the sample size, the sample representativeness, the protocol and the statistical assumptions before believing a single pixel of it.“
By the end of August both prayers had been answered. The proposal below is smart, feasible, and has great potential. Can we publicise it and help implement it?
Cogn Affect Behav Neurosci. 2013 Aug 28. [Epub ahead of print]
How to produce personality neuroscience research with high statistical power and low additional cost.
Department of Psychology, York University, 4700 Keele St. W., Toronto, ON, M5T2X5, Canada, firstname.lastname@example.org.
Personality neuroscience involves examining relations between cognitive or behavioral variability and neural variables like brain structure and function. Such studies have uncovered a number of fascinating associations but require large samples, which are expensive to collect. Here, we propose a system that capitalizes on neuroimaging data commonly collected for separate purposes and combines it with new behavioral data to test novel hypotheses. Specifically, we suggest that groups of researchers compile a database of structural (i.e., anatomical) and resting-state functional scans produced for other task-based investigations and pair these data with contact information for the participants who contributed the data. This contact information can then be used to collect additional cognitive, behavioral, or individual-difference data that are then reassociated with the neuroimaging data for analysis. This would allow for novel hypotheses regarding brain-behavior relations to be tested on the basis of large sample sizes (with adequate statistical power) for low additional cost. This idea can be implemented at small scales at single institutions, among a group of collaborating researchers, or perhaps even within a single lab. It can also be implemented at a large scale across institutions, although doing so would entail a number of additional complications.
- [PubMed - as supplied by publisher]