Editorial, Spring 2020

At the beginning of 2019, the editorship of Psychometrika changed: We, the authors of this editorial, were taking on the journal as executive editor and editor of the Theory and Methods section, as well as the section editor of the Application Reviews and Case Studies. Instead of writing about something that we did not yet know about, we decided to run an editorial about how the journal will be led after having spent some time in this role.

Working in 2019 with past editors, the editorial council, the secretary, and the current, past, and incoming president(s) of the Psychometric Society, we felt that the journal is well-advised to adjust to the changing landscape of publishing. In 2020, we will introduce a couple of innovations to Psychometrika. After attending the highly successful conference in Santiago de Chile, we feel reassured that the annual meeting is an important opportunity to meet colleagues and discuss future directions. The local organizers and all involved at the society made this conference an event that was well-worth traveling to. This meeting was providing the space that allowed us to more fully develop ideas for topics the journal should cover in some more depth. Below, we describe how we plan to move Psychometrika forward in order to better serve the current readership while at the same time aiming to broaden the scope and interest in the journal.

Special Issues

Psychometrika was long known to many as ‘the journal that does not do special issues,’ which was kind of true for all practical purposes, but not when considering the monographs, the journal put out over the years. The Psychometric Society webpage provides access to these freely at:

https://www.psychometricsociety.org/content/free-articles-monographs

While the Psychometrika Monographs were (by definition) not multi-authored, these monographs (for example, Samejima 1969) took a relevant topic of broader interest and illuminated it in greater depth, carving out the required material and developing it across multiple chapters. Such an approach is also possible by selecting multiple contributions that are aligned with a common topic and that jointly can cover greater depth and breadth than what would be possible in a single article.

Therefore, through many discussions with scholars, three proposals for special issues were developed, covering emerging topics as well as issues of continued interest. Over the next year, there will be collections of articles be published on:

• 1. Invited special section in ARCS: Applying psychometric methods to assessing patient-reported outcomes: Lessons learned from the Patient-Reported Outcomes Measurement Information System (PROMIS®) initiative. (Guest Editors: Bryce Reeve, Ronald Hays)

• 2. Open call special issue in ARCS: Psychometric Network Models (Guest Editors: Maarten Marsman, Mijke Rhemtulla)

• 3. Open call special issue in ARCS and T&M: Models for Intensive Longitudinal Data and Forecasting (Guest Editors: Peter Halpin, Siwei Liu, Kathleen Gates)

The special ARCS section on invited PROMIS researchers to take a critical look at and report what they have learned in the applications of psychometric methods to PRO over the last 15 years. Discussion and rejoinder for the articles were also planned. Open calls for the other two special issues were distributed by email to current and recent members of the psychometric society. These were also published on the website of the Psychometric Society and the journal. The special issue guest editors received a large number of proposals and are currently working to select topics for these exciting special issues. We are confident that the final product from the special issue/section will be a very valuable resource for psychometricians around the world.

Application Reviews and Case Studies (ARCS)

While the ARCS section was announced back in 2003, many probably still perceive the section to be a relatively new addition to the journal. We would like to take this opportunity to clarify the mission of the section. As modern data collection technologies advance, data are now being collected both rapidly and in large amounts. Many substantive studies in psychology, education, and social and behavioral sciences are increasingly relying on efficient and accurate data analytic methods. Examples include analyses of machine-collected data from neuroscience, large-scale multinational and multiwave educational assessments, measurement and analyses of self-reported outcomes using mobile devices in health sciences, and customer relationship management and marketing data analytics. In the words of our original announcement, the target of the ARCS section is the locus of the intellectual crossroads between psychometric methodology that inspires substantive work and substantive work that inspires psychometric methodology, which is more important today than ever before. We welcome two categories of articles: First, application reviews, which include reviews of broad modeling and data analysis approaches that cut across multiple domains in psychological, educational, social, and behavioral sciences; or reviews of multiple methods that can be applied to solve the same specific problem. Application reviews are expected to offer insight into the connection between these approaches. We also welcome case studies, namely applications of quantitative modeling or data analysis to empirical studies in psychology and related fields. This would include utilization of a data set of significance as well as demonstrating that the study is illustrative of an approach that goes beyond evident applications of well-known methods. Specifically, we appreciate applications that incorporate new and extended features to existing psychometric methods or adaptation of existing psychometric methods to a new field, or new data type collected in the same field (e.g., new kind of data collected using new technology).

New Book Review Editor

The book reviews published in Psychometrika are an important resource for researchers allowing them to learn about new publications through an evaluation provided by an independent scholar. We can certainly speak for the whole leadership and the members of the Psychometric Society when thanking Jeff Harring here for his service in this role that brought us many interesting book reviews. Jeff has graciously accepted an invitation to serve as associate editor and was replaced by Marten Marsman as new book editor of the journal. We are looking forward to seeing many more interesting book reviews in future issues of Psychometrika.

With this, we would also like to ask readers to submit titles that may be of interest for the readership of the journal. Whether you have read the book yourself, or you learned about an upcoming title, please feel free to submit your suggestion for book reviews to

reviews@psychometrika.org

Changes to the Website and How Psychometrika Sections are Presented

Article categories such as the Theory and Methods section and the Application Reviews and Case Studies section are intended to allow for greater breadth of the materials that can be submitted to Psychometrika. However, these categories were (unintentionally) not provided in the online presentation of the articles, so they were unavailable to help guide readers when studying the content of the journal. This was recognized as an issue that needed remediation as readers and submitting authors repeatedly requested information about which articles would be considered ARCS or T&M, respectively.

As part of the redesign, the publisher conducted in order to improve the presentation of journal-related information, it was agreed that the T&M section, the ARCS section, and book reviews will be clearly identified, so that readers can immediately see which section any current and future article belongs to. This will allow to gain insight into what types of papers are typically published in the different sections and will potentially help to identify what other topics should be promoted and how these should be covered in the journal.

Use SharedIt to Make Articles Broadly Accessible

Springer Nature is the publishing house supporting the production of Psychometrika. Springer Nature has recently made available a new technology that allows readers with access to the Journal to share a link with colleagues that allows online reading, even if these colleagues would not have access to the journal through other avenues. The screenshot below shows the article information for Heiser and Hubert (2016) and includes such a link that can be generated and used through this SharedIt technology.

As Springer Nature describes the approach:

SharedIt: Springer Nature’s SharedIt feature allows researchers to share links to view-only; full-text subscription research articles can be posted anywhere—including on social media platforms, author websites and in institutional repositories—so researchers can share research with colleagues and general audiences. The more papers from the journal are disseminated with other researchers, the more opportunities there are for papers from the journal to get cited. Additional information about SharedIt can be found at the following link: https://www.springernature.com/gp/researchers/sharedit.

We are very excited about these new features of the journal and invite you to try these out. Please use the SharedIt links whenever you want to make someone aware of a journal article of interest. These can of course also be shared via social media such as Twitter, LinkedIn, Facebook, and others. The year 2020 caused confusion about whether the new decade starts, or whether it starts in 2021, but one thing is certain, Psychometrika will turn 85 in 2021 and we look forward to working toward a successful and bright future of the journal.

We would like to involve readers by requesting suggestions, not only for books that should be reviewed, but also if you feel that certain topics that are relevant to current and future developments of the field are not covered sufficiently. Please feel free to contact us and suggest topics you would like to see tackled in the journal.

Matthias von Davier & Edward Ip