Monthly Archives: September 2016

Tone Deaf

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In my field of psychological science there have been many discussions the past few years on the way an argument is expressed, its tone. A common theme is the general desire for academic discussions to be positive and respectful, and not mean and antagonistic. With the release of Susan Fiske’s commentary on the state of scientific communication (see a detailed discussion of the commentary in the context of other developments in the field the past decade here), the discussion of “tone” has heated up again. This is particularly true for the Facebook discussion group “PsychMap” where the tone of communication is closely monitored.

The following of course is simply my own opinion, and I respect that others disagree with this opinion, but I do not really care that much about the tone of an argument. A person can offer up a positive, or neutral, argument and be full of shit, or not. A person can offer up a negative, sarcastic, even rude argument and be on the mark, or not. If you have sat through a few faculty meetings  you will know exactly what I mean. Personally, I do my best (and sometimes my best is not good enough, to be honest) to focus on the argument being presented and not on how the argument is presented. I can only control (a) how I decide to put forward my own arguments (asshole or angel, or somewhere in between), and (b) how I respond to others’ arguments. In my opinion the tone of argument reflects more on the person delivering the argument than on the target of the argument. I accept that if I choose to deliver my arguments in a manner most of my colleagues would perceive as obnoxious and combative that I may not be taken so seriously by these colleagues for very long. I personally therefore choose to be positive, or at least direct in a fairly neutral manner, with the majority of my arguments (hopefully as reflected in my blog posts the past year and a half, and in my papers on meta-scientific issues). I therefore prefer discussions not to be officially moderated, and to let people own the words they choose to use to present their views. The field of academic psychology is literally a community of highly educated individuals that are smart enough to know the difference between shit and Shinola; we can figure out if an argument, however presented, has substance or not.

And for what it’s worth, it seems to me that the majority of discussions I am privy to in private and on social media are positive and constructive in tone. That is nice.

 

Organize your Data and Code for Sharing from the Start

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On September 12, 2016, experimental psychologist Christopher Ferguson created a “go-fund-me” page to raise funds for access to an existing data set that was used to advance scientific arguments in a scientific publication (link here). In Ferguson’s own words: “So I spoke with the Flourishing Families project staff who manage the dataset from which the study was published and which was authored by one of their scholars.  They agreed to send the data file, but require I cover the expenses for the data file preparation ($300/hour, $450 in total; you can see the invoice here).” Ferguson’s request has generated a lot of discussion on social media (this link as well), with many individuals disappointed that data used to support ideas put forward in a scientific publication are only available after a big fee is paid. Others feel a fee is warranted given the amount of effort required to put together the data requested into one file, as well as instructions regarding how to use the data file. And in the words of one commenter, “But I also know people who work with giant longitudinal datasets, and preparing just the codebook for one of those, in a way that will make sense to people outside the research team, can take weeks.” (highlighting added by me).

As someone that has collected data over time from large numbers of romantically involved couples, I agree that it would it take some time to prepare these data sets and codebooks for others to understand. But I think this is a shame really, and is a problem in need of a solution. If it takes me weeks to prepare documentation to explain my dataset organization to outsiders, I am guessing it would take the same amount of time to explain the same dataset organization to my future self (e.g., when running new analyses with an existing data set), or a new graduate student that wants to use the data to test new ideas, not to mention people outside of the lab. This seems highly inefficient for in-lab research activities, and represents the potential loss of valuable data to the field given that others may never have access to my data in the event that (a) I am too busy to spend weeks (or even hours for other data sets) putting everything together for others to make sense of my data, and (b) I die before I put these documents together (I am 43 with a love of red meat, so I could drop dead tomorrow. I think twice before buying green bananas).

So what is my proposed solution? Organize your data and code from the start with the assumption that you will need to share this information (see also “Why scientists must share their research code”). Create a data management plan at the beginning of all your research projects. Consider how the data will be organized, where it will be stored, and where the code for data cleaning/variable generation, analyses, and plots will be stored. Create meta-data (information about your dataset) along the way, updating as needed; consider where to store this meta-data from the beginning. If you follow these steps, your data, meta-data, and code can be available for sharing in a manner understandable to other competent researchers in a matter of minutes, not weeks. Even for complex data sets. Your future self will thank you. Your future graduate students will thank you. Your future colleagues will praise your foresight long after you are dead, as your [organized] data will live on.

Update: see Candice Morey’s post on the same topic.

 

How to Publish an Open Access Edited Volume on the Open Science Framework (OSF)

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Edited volumes are collections of chapters on a particular topic by various experts. In my own experience as a co-editor of three (3) edited volumes, the editors select the topic, select and invite the experts (or authors), and identify a publisher. Once secured, a publisher typically offers a cash advance to the editor(s) along with a small percentage of sales going forward in the form of royalties. The publisher may also provide reviewing services for the collection of chapters, and will advertise the edited volume when it is released. The two primary ways for consumers to access the chapters is to (a) purchase the book, or (b) obtain a copy of the book from a library.

With technological advances it is now possible to publish edited volumes without a professional publishing company. Why would someone choose to not use a publishing company? Indeed, they are literally publication experts. Perhaps the biggest reason is that the resulting volume will be open access, or available to anyone with a connection to the internet, free of charge. There are also some career advantages to sharing knowledge open access. Also, a publishing company is simply not needed for all publication projects.

There are very likely many different ways to publish an edited volume without using a professional publishing company. Below, I outline one possibility that involves using the Open Science Framework (OSF). Suggestions for improving these suggested steps are welcome.

Steps to Using the OSF to publish an Open Access Edited Volume

  1. Identify a topic for the edited volume, and then identify a list of experts that you would like to invite to contribute chapters.
  2. If you do not have an OSF account, create one (it is free). Create a new project page for your edited volume, and give it the title of the proposed edited volume. Select one of the licensing options for your project to grant copyright permission for this work.
  3. Draft a proposal for your edited volume (e.g., the need for this particular collection of chapters, goals of the volume, target audience, and so on). Add this file to the project page.
  4. Send an email inviting potential authors, providing a link to your OSF project page so they can read your proposal.
    • You can make the project page public from the start and simply share the link, or,
    • You can keep the project page private during the development of the edited volume and “share” a read-only link to the project page with prospective authors only.
  5. Ask all authors that accepted the invitation to create on OSF account. Then create a component for each individual chapter; components are part of the parent project, but are treated as independent entities in the OSF. Use the proposed title for each chapter as the title of the component. Add the author(s) as administrators for the relevant component (e.g., A. Smith has agreed to author chapter #4; add A. Smith as an administrator of component #4).
  6. Ask authors to upload a copy of their first draft by the selected deadline. Provide feedback on every chapter.
    • One option is to download a copy of the chapter, make edits using the track changes option, and then upload a copy of the edited chapter using the same title as the original in order to take advantage of the “version control” function of the OSF (i.e., all versions of the chapter will be available on the project page in chronological order, with the most recent version at the top of the list).
  7. Ask authors to upload their revised chapter using the same title (again to take advantage of the “version control” function of the OSF).
  8. When the chapters are completed, “register” the project and all components. This will “freeze” all of the files, meaning changes can no longer be made. The registered components, or chapters, represent the final version of edited volume. Then…
    • Make all of the components, as well as the main project registration, public;
    • Enable the “comments” option so that anyone can post comments within each component (e.g., to discuss the material presented in the chapter);
    • Click the link to obtain a Digital Object Identifier (DOI) for each component (i.e., chapter).
  9. Advertise the edited volume
    • Use social media, including Facebook discussion groups and Twitter (among others). Encourage readers to leave comments for each chapter on the OSF pages;
    • Ask your University to issue a press release;
    • Ask your librarian for tips on how to advertise your new Open Access edited volume (librarians are an excellent resource!!).

Prior to following these steps to create your own Open Access edited volume on the OSF (or by using a different approach), there are some pros and cons to consider:

Pros

  • You have created an edited volume that is completely Open Access
  • The volume cost no money to create, no money to advertise, and no money to purchase
  • Given that the chapters are available to a wider audience than a traditional edited volume released by a for profit publishing company, it is likely that they will actually reach a wider audience as well and have a greater scientific impact

Cons

  • You do not receive a cash advance or royalties
  • You do not receive any assistance from a publisher for reviewing or advertising
  • This approach is new compared to traditional publishing, and therefore you may be concerned that you will not receive proper credit from others (e.g., people evaluating your contributions to science when deciding to hand out grant funds, jobs, promotions, and so on)

Final Thoughts

There is usually more than one way to achieve the same aim. Professional publishing companies work with academics to create many edited volumes every year, but creating an edited volume does not inherently require the assistance of a professional publishing company. The purpose of this post was to present one alternative using the functionality of the Open Science Framework to publish an edited volume that is Open Access. I am sure there are even more ways to achieve this aim.

How much Research is Confirmatory Versus Exploratory?

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The president of APS is nervous about pre-registration, or the idea of writing down study goals and hypotheses prior to collecting and/or analyzing data. One concern is that we do not have any data on whether or not pre-registration puts limits on exploration within research programs. If researchers are required to pre-register study goals and/or hypotheses, and given that in many instances good ideas are developed after seeing the data (not always before), then many good ideas may never be tested. This is of course a fair question worthy of discussion.*

But what we perhaps need to know first is approximately how much of our collective research is exploratory at present? We know that over 90% of all journal articles report statistically significant effects (no citation required), presumably for hypotheses developed prior to data collection. If so, then these data analyses have been presumably conducted in a confirmatory manner (i.e., to test hypotheses developed prior to data collection and/or analyses). Pre-registering these confirmatory hypotheses should therefore not be problematic or stifle discovery, particular given current options that make pre-registering hypotheses very easy (e.g., the Open Science Framework, aspredicted.org). If these confirmatory hypotheses took time to develop via exploratory research, then this suggests a massive amount of exploratory research is currently not being reported in any publication outlet; this research represents the large part of the iceberg hidden beneath public perception, with the small confirmatory bit of research peeking into public awareness. If so, we should collectively figure out a way to make this large body of exploratory research, and the details of how these explorations helped researchers develop their confirmatory hypotheses, publicly available. This is important stuff!**

To the extent the current literature, however, is not primarily presenting a priori hypotheses and confirmatory data analyses, then it will contain a blend of confirmatory hypotheses and hypotheses developed during and/or after data analyses (i.e., exploration within the research program). Given that over 90% of all journal articles report statistically significant effects, and that not all articles contain sections that clearly delineate confirmatory hypotheses and those developed from exploration with the data being presented, it is therefore an open question of how much research is confirmatory versus exploratory. Pre-registration of study goals and/or hypotheses, both confirmatory and exploratory (and everything in between), may be one way to answer this question. And perhaps before setting up large scale randomized control trials to determine if pre-registration can limit exploration, we should know just how much exploration is actually going on, as well as the links between this exploration and confirmatory hypotheses that are subsequently developed. Many of us seem to agree that exploration is very important, so let’s make an effort to document our explorations more clearly and openly.

 

* Russ Poldrack is on record as not being nervous about pre-registration

** “stuff” is a technical term of course