Reinbergs Lab manual

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This page is currently in draft form.

Last updated: 2025-06-02.

This manual documents common ways of work, as well as tips for success. It's based on my workflows (and thus the workflows I encourage by lab to use) but it may be useful for others as well. Feel free to take what you like and ditch the rest.

General information

The lab is housed in USU's Department of Psychology and led by Dr. Reinbergs. We study suicide and related concerns (e.g., nonsuicidal self-injury, depression, borderline personality symptoms, behavior therapies), particularly among youth (broadly defined). We keep an eye toward how our research can align with interventions in various settings, especially schools. Our work spans several domains including studies relevant to conceptual, epidemiological, clinical, and measurement aspects of suicide. Our ultimate goal, inspired by Marsha Linehan, is to help youth build lives worth living.

The lab consists of Dr. Reinbergs and several PhD students in the School Psychology program at USU. EdS students from the school psychology program are also sometimes involved, particularly in supporting PhD students.

Ways of work

The following sections detail our common ways of work.

Communication

Digital communication is accomplished using Microsoft Teams chat via our USU accounts. This helps us keep a more focused record of communication than email inboxes. In the general channel, I often post trainings, new articles, and celebrations that are likely relevant to most lab members. You can also call or text my cell phone for emergencies.

Please respond to messages/emails from Dr. Reinbergs by the end of the next business day. For example, if you get an email from me on Friday, I expect you to respond by 5pm Monday. I will hold myself to the same standard. Given the flexible nature of academic work, I sometimes send emails after hours or on weekends. Please do not take this to mean I expect a response after work hours or on the weekend.

We meet in person as a lab each week. These meetings help us stay up to take, problem solve, and support each other. I strive to make the lab meetings supportive, collaborative, and non-competitive.

Digital files

All lab files are in a shared USU Box folder, which can also be accessed via Teams. Some projects (e.g., with restricted data) may involve additional security practices. Files are organized in project folders. Each project folder has subsections including data, analysis, plots, manuscript, scratch, and posted. Files are descriptively named with dashes instead of spaces. More on best practices in project file organization and styling can be found in Chapter 9 of Data Management in Large-Scale Education Research by Crystal Lewis. Carefully organizing your work is always worth the effort.

Research software

We depend on several key pieces of research software in addition to Microsoft Teams for communication and Box for file storage. Lab members are expected to become comfortable with these programs. The Resources section of the manual below provides links to tutorials that may be helpful.

Zotero

Zotero is a powerful reference management program. It is used to organize journal article PDFs, generate both in-text citations and reference sections, and has useful abilities for annotating PDFs. It is free, open-source, and provides a Microsoft Word plugin that is essential when drafting manuscripts. Although Zotero is free, you may want to consider paying for the subscription that syncs/backs up your Zotero library for peace of mind and to support the project.

R/R Studio/Positron

We primarily use the R statistical environment for analyses. R is an open-source scripting language that is especially suited to working with data, conducting statistical analyses, and reporting/visualizing results. R packages are available for even the most cutting edge statistical methods. It is highly used in many academic fields, including psychology, as well as in industry settings. R Studio is an integrated development environment (IDE) that improves quality of life when working with R. It is also open-source. You need to install the latest version of R, then install R Studio. If you wish, you can also install a next-generation IDE called Positron, which is currently in beta but will eventually replace R Studio.

There are several R packages that you may find useful, in no particular order.

lavaan: For structural equation modeling.
psych: For exploratory factor analysis and classical psychometrics.
data.table: For data management. Alternatively, you may prefer the dplyr package if you are more comfortable with the tidyverse.
ggplot2: For plotting.
gtsummary: For creating standard summary tables (e.g., balance tables, regression tables, demographics tables). Built on the gt package, which you can use for more customized tables.
fixest: Regression modeling (including logistic regression, and negative binomial regression, and regression with robust standard errors).
brms: Bayesian modeling in a more user friendly framework.
easystats: A collection of packages with many convenience functions.
rblimp: Modern missing data handling and Bayesian modeling. For straight forward multiple imputation methods, there is also the mice package.
survey: For analysis of complex survey data. There is also a tidyverse/dplyr-style wrapper called srvyr discussed in the free book Exploring Complex Survey Data Analysis Using R.
marginaleffects: For interpreting regression models, calculating marginal effects, marginal predicted probabilities etc.

Other statistical software

Although we try to stick to R, Dr. Reinbergs also has access to the latest versions of Stata and Mplus. Sometimes things are more straight forward in Stata than R depending on the task. Or the command in Stata may be more well documented than in R. In situations where Stata has a well developed feature, we may test our R results against the Stata results to ensure accuracy.

A note on AI

USU has made enterprise Microsoft Copilot accounts available to all users. These accounts run a modified ChatGPT 4 model. Our enterprise agreement states that Microsoft will not use our data to train their models. Despite this, under no circumstances should you upload raw data or anything potentially identifiable or otherwise private to any generative AI services including Microsoft Copilot with your USU account. Under no circumstances should you write any professional/academic/clinical documents using generative AI. This has the potential to be a huge threat to all of our credibility and depending on the circumstance could be a very serious ethical violation.

That said, there are some use cases where generative AI services may be helpful, particularly in coding. AI is safest when you can immediately verify that its solutions work. An example is using AI to help you create a particular plot using ggplot2. Because you can immediately run the AI generated solution and see if it creates the plot you want, you instantly know whether the AI generated solution is true.

GitHub offers free pro accounts to university students. These accounts come with access to GitHub Copilot, which comes with access to nearly all major AI models. For example, it provides access to Anthropic's Claude Sonnet 3.7 Thinking model that is far better at R tasks than Microsoft Copilot or ChatGPT 4.1.

Git/GitHub

As noted above, university students get free pro accounts on GitHub. Git itself is open-source and free. Admittedly, git has a steep learning curve and might not be worth it for every project. It is, however, a powerful way to implement version control and work on analysis files with collaborators. Git functionality is also implemented in both R Studio and Positron with GUIs. GitHub Desktop is a git GUI that is also free and works both with local repositories and GitHub repositories.

Google Scholar & ORCID

Google Scholar is academia's default service for tracking publications and citations. Keep your google scholar account up to date as many academics use these accounts to view your work. Additionally, when searching for literature using Google Scholar, you can connect your account to USU library services to get legal access to many of the articles you'll find while searching.

Increasingly, journals and other services also use ORCID to properly identify authors. This is a useful service that is free and worth signing up for. For example, if you list your ORCID in addition to your USU email on a publication, people will still be able to reach you when you no longer have access to your USU email.

Authorship

I expect PhD students to lead their own manuscripts and to be authors on manuscripts with myself or other lab members. We follow APA guidance on establishing authorship credit (see below) We strive to establish whether authorship is warranted and authorship order as early in the research process as possible to foster transparency and prevent misunderstandings. If you have concerns about authorship, please bring them up to Dr. Reinbergs.

Authorship is reserved for persons who make a substantial contribution to and who accept responsibility for a published work. Individuals should take authorship credit only for work they have performed or to which they have substantially contributed (APA Ethics Code Standard 8.12a, Publication Credit). Authorship encompasses, therefore, not only those who do the writing but also those who have made substantial scientific contributions to a study. Substantial professional contributions may include formulating the problem or hypothesis, structuring the experimental design, organizing and conducting the statistical analysis, or interpreting the results and findings. Those who so contribute are listed in the byline. Lesser contributions, which do not constitute authorship, may be acknowledged in the author note... Lesser contributions may include such supportive functions as designing or building the apparatus, suggesting or advising about the analysis, collecting or entering the data, modifying or structuring a computer program, recruiting participants, and obtaining animals. Conducting routine observations or diagnoses for use in studies does not constitute authorship. Combinations of these (and other) tasks, however, may justify authorship.

Open science

As a lab, we try to adhere to principles of open science. This means making our work and decision making process transparent and publicly available. We do so by using preprints and by making our analysis code, analysis output, and data (if allowable) public. We host preprints, analysis code/output, and data on the Open Science Foundation website for the lab. We pre-register some projects on OSF as well.

Secondary data

Lab members are encouraged to conduct studies with secondary data. This could be data collected by the lab for a different project, data from outside the lab that was publicly shared by another researcher, or national/state-level datasets. Particularly in suicide research where primary data can be difficult to collect, secondary data allows us to explore many important questions. Secondary datasets can also be rich sources of data for psychometrics projects. Additionally, even if a question has been examined in secondary data before, reproducing this analysis with more robust methods or examining whether the findings hold in a different dataset represent important contributes to the literature. Dr. Reinbergs has access to many different datasets that contain suicide / mental health variables.

Getting to know the field(s)

One of the great things about this work is that is it relevant across many fields. We sit somewhere between clinical psychology (particularly behavior therapies and developmental psychopathology), school psychology (youth mental health, prevention service models, and school-based interventions), and suicidology.

Organizations and conferences

ABCT: Association of Behavior and Cognitive Therapies. Mostly clinical psychology. There are often suicide/self-harm/depression/BPD researchers presenting at the annual conference. There is also always a pre-conference day on DBT hosted by ISIT-DBT.

NASP: National Association of School Psychologists. This is the national school psychology organization / annual conference. Mostly focused on practitioners.

IASR: International Academy of Suicide Research. Conference every two years that is the most research-focused suicide conference in the field.

SRS: Suicide Research Symposium. An excellent, free, online annual conference for suicide researchers sponsored by the American Foundation for Suicide Prevention.

Conferences and professional organizations in related fields include AERA (education, applied measurement), ABAI (behavior analysis), APS (psychology research from multiple fields), ACBS (ACT / contextual behavior science), APA (psychology research from multiple fields), and the Advancing School Mental Health Conference from the National Center on School Mental Health.

Relevant companies include Behavior Tech (DBT) and CAMS-Care.

Journals

There are a seemingly endless number of journals out there, many of them predatory or not well regarded. Here are a sampling of legitimate journals within our related subfields—although there are of course many more!

Suicidology: Suicide and Life-Threatening Behavior, Crisis, Archives of Suicide Research, Death Studies.

School psychology: School Psychology, School Psychology Review, Contemporary School Psychology, Psychology in the Schools, School Mental Health, Assessment for Effective Intervention, Journal of Applied School Psychology, Journal of Psychoeducational Assessment, Journal of Educational and Psychological Consultation.

Child Clinical: Child & Family Behavior Therapy, Evidence-Based Practice in Child and Adolescent Mental Health, Journal of Clinical Child & Adolescent Psychology,

Currently (following the sale of, and subsequent demise of, twitter), the most robust academic community on social media is found on Bluesky. I have learned so much from members of academic twitter/bluesky. I highly recommend following researchers and topics you care about. You can start by following accounts that I follow, look for starter packs of researchers to follow, or browse hashtags like #rstats. Reminder that social media is public, so be ethical in your posts etc.

Professional reputation

The fields of school psych, child clinical psych, and suicidology are all small. Your professional reputation is extremely important to your success. You do not have to look far to find examples of unethical researchers and clinicians. Do not sacrifice your professional reputation for anyone. Your professional reputation is more important than a grade or looking smart or having the last word. Never, ever claim work that is not your own. Treat everyone well. Fostering this trust is also important for the public to have trust for the profession of psychology and for science in general. If you feel you may be walking into something in an ethical grey area, or have an ethics question, notify Dr. Reinbergs immediately.

Onboarding

When joining the lab, please complete the following tasks:

Complete USU's CITI training (or transfer your previous CITI training).
Email Dr. Reinbergs from your USU email to remind him to add you to the lab Microsoft Teams.
Send Dr. Reinbergs your CV and CITI training certificates via Teams so Dr. Reinbergs can keep them on file.
Create accounts in Google Scholar, GitHub, OSF, and ORCID if you have not already. If you already have these accounts, add your USU email to them.
1. In Google Scholar, add the USU library to your profile. Settings > Library links > type USU and add all > Save.
Download and install the software we use: Zotero, R, R Studio and/or Positron.
1. You can also consider signing up for a paid Zotero account so that your files are synced across computers / backed up, but this is not required.
2. Also download Microsoft Teams and the Box desktop sync app if you haven't already.
Send a photo and 2-3 sentence bio to Dr. Reinbergs so he can add you to the people section of the lab website. If you do not want to be included on the website, that is fine — just send Dr. Reinbergs a message that you do not wish to be included.

More resources

I have a book buying habit and am constantly bookmarking links to useful tutorials for all kinds of things. Please ask me for resources for things you want to learn, whether that is data management in R, different statistical analysis methods, manuscript writing, clinical resources, key literature for a lab topic etc. A key to success in grad school is identifying the right resources and diving in!