Workshops

DGPs 2020 offers a number of pre-conference workshops. You will be able to register for the workshops in April/May. Access to the workshops is limited and you can participate on a first come, first serve basis.

Workshop | Scientific Writing (Meule)

30 participants | Saturday, September 12th, 2020 | 14.00 - 17.30h

The ultimate goal of a scientific study is to publish the results in theform of a journal article. This workshop will give guidance on the entire process from writing a research paper to its final publication. The topics covered in this workshop will range from more general tips on writing style and structure to specific guidelines on how to present results in the form of tables and figures or on language issues including punctuation. Beyond manuscript preparation, the workshop will also include information on the submission, revision, and publication process such as selecting the right journal, dealing with reviewers' comments, and issues during copy editing. The overall aim is to enable young scientists to write with confidence and rigor and, therefore, to eventually increase success in getting their manuscripts published.

Workshop | Metacognitive Therapy for OCD (Kleiman)

40 participants | Saturday, September 12th, 2020 | 14.00 - 17.30h

Many patients with obsessive-compulsive disorder benefit from psychotherapeutic treatment, but a not insignificant percentage discontinue the therapy prematurely or do not respond to the treatment offered. Metacognitive model and treatment approaches for obsessive-compulsive disorder promise a treatment that is both effective and easier for patients and therapists to manage. Metacognitive therapy (MCT) according to Adrian Wells is a further development of cognitive behavioural therapy. This form of therapy focuses on metacognitive beliefs and processes as causes of mental disorders. In contrast to the original cognitive therapy, it focuses less on the content of cognitions and more on the processes of thinking and beliefs about one's own pathological thinking that control these processes. The metacognitive model of obsessive-compulsive disorder and its therapeutic elements are demonstrated in a practice-oriented manner and their application is practiced in small groups. These include attention techniques, Detached Mindfulness (DM), exploration and modification of metacognitions and behavioural experiments. Participants have the opportunity to try out the interventions presented in role-plays and reflect on them in the group. The transfer to the participants' respective fields of work will be acknowledged and the possibilities of integrating the metacognitive methods into already existing treatments will be discussed.

Workshop | Integrating compassion oriented interventions into daily psychotherapeutic work - Mitgefühlsorientierte Interventionen für die psychotherapeutische Praxis (Stierle)

30 participants | Saturday, September 12th, 2020 | 14.00 - 17.30h

Experiences of shame and devaluating self-criticism are common phenomena in daily psychotherapeutic work across disorders. Especially Depression, Social Phobia, OCD and BDD as well as BPS are often associated with the processes above. Recent research suggests benefitial effects including compassion oriented interventions into standard psychotherapeutic work (e.g. Hofmann et al., 2012; Foroughi et al., 2019; Arimitsu et al., 2018). Within the workshop participants will learn how to integrate compassion interventions in their therapeutic work deriving techniques from Compassion Focused Therapy (Gilbert, 2013) as well as Mindful Self-Compassion (Neff & Germer, 2018). Techniques will include soothing rhythm breathing and imagery work as well as chairwork and compassionate letter writing. Special focus is put on the psychoeducational, evolutionary background of compassion and its implications for the motivation and willingness to apply these interventions. Participants will engage in group discussion and individual excercises.

Workshop | Datenaufbereitung und deskriptive Statistik in R (Yanagida)

Please bring your laptop - with R installed | 30 participants | Saturday, September 12th, 2020 | 14.00 - 19.30h

R ist eine Open-Source-Software für Datenmanipulation, Durchführung statistischer Analysen und grafischer Darstellung von Daten, die zunehmend Verbreitung in der universitären Ausbildung und Forschung findet. Die Teilnehmenden dieses Workshops erhalten eine Einführung in diese freie Programmiersprache und Softwareumgebung mit Schwerpunkt auf Datenaufbereitung und deskriptive Statistik unter Verwendung des neu entwickelte R-Pakets misty (Yanagida, 2020). Im ersten Schritt dieses Workshops werden Grundlagen von R (z. B. Funktionen, Datentypen, Datenstrukturen etc.) wiederholt, um fortgeschrittene Inhalte (z. B. Umgang mit Zeichenketten etc.) einzuführen. Nachfolgend wird anhand eines praktischen Beispiels die Aufbereitung eines Rohdatensatzes aus einem Online-Fragebogen zu einem analysefertigen Datensatz (z. B. Umbenennung von Variablen) und Export zu anderen Statistik-Programmen (SPSS oder Mplus) demonstriert. Zuletzt wird die deskriptive Analyse der Daten in Bezug auf Tabellen (z.B. Kontingenztafel) und statistischer Kennwerte (z. B. Korrelationsmatrix) besprochen. Zuletzt wird ein Rohdatensatz bereitgestellt, anhand dessen der Prozess der Datenaufbereitung und die Durchführung deskriptiver Analysen geübt werden soll. Dieser Workshop richtet sich an Personen, die über grundlegende Kenntnisse in R verfügen und bereits erste Erfahrungen im Umgang mit diesem Programm gesammelt haben.

Workshop | Multinomial-Processing-Tree Modeling: Basic Methods and Recent Advances (Erdfelder, Heck, Meißner)

Please bring your laptop - with R installed | 30 participants | Saturday, September 12th, 2020 | 14.00 - 19.30h | Sunday, September 13th, 2020 | 9.30 - 17.30h

In several fields of psychology, MPT models have proved to be powerful tools to disentangle different cognitive processes contributing to the same observable responses. Importantly, recent research resulted in sophisticated improvements and extensions that broaden the field of potential applications significantly. Moreover, user-friendly software now lowers the barriers of application. Overall, MPT models have become promising and easy-to-use instruments for substantive researchers to test psychological theories. The two-day workshop on the basics and advances in MPT modeling will be largely application-oriented. Nevertheless, we will provide a solid conceptual and statistical treatment. For participation, basic knowledge about MPT models is useful but not necessary (a solid background in statistics is sufficient). Note that this workshop addresses both substantive and methodologically oriented researchers who want to learn about recent MPT developments in addition to researchers who have been interested in MPT modeling but did not know how to start.

An analogous workshop was planned for the TeaP 2020 conference in Jena but cancelled due to the corona crisis. However, the description still applies to the Vienna pre-conference workshop:
https://teap2020.dryfta.com/79-program/87-pre-conference-workshop
The number of participants is limited. We recommend early registration.
This workshop is supported by the William K. & Katherine W. Estes Fund.
The Estes Fund is jointly overseen by the Association for Psychological Science and the Psychonomic Society. For more information, see https://www.psychologicalscience.org/members/awards-and-honors/estes-fund

Workshop | A beginner’s guide to R and JAMOVI (Berkessel, Brohmer)

Please bring your laptop | 30 participants | Sunday, September 13th, 2020 | 9.30 - 13.00h

The statistical computing software R is increasingly popular among psychological researchers. R owes its popularity to several aspects: First, R is free to download, making it more inclusive and researchers non-reliant on their institutional funding. Second, open-source allows R users to conveniently conduct transparent and reproducible analyses. Third, R is powerful as there are many statistical add-ons (“packages”) that include way more statistical approaches than traditional programs. Fourth, there is also R-based software available – JAMOVI and JASP – that provide easy-to-use graphical user interfaces. Fifth, the ever-growing R users community offers thorough documentation and quick help.
Throughout the last years, proficiency in R has become a prerequisite for many Ph.D. students, as well as for a scientific career thereafter. Therefore, this workshop will provide an easy-to-follow introduction to R and JAMOVI for complete beginners, which may motivate an easy transition to these programs. Participants will learn how to load data into these programs before pre-processing it. Afterward, some analyses will be performed, introducing basic functions and packages that are provided by the respective program. In the second part, we will give a short overview of how to present statistical output using informative figures and tables. In the end, we will recommend some advanced packages that will make a researcher more reproducible and transparent in the long-run. In conclusion, we provide an intelligible hands-on introduction to R and JAMOVI that enables interested researchers to start using these programs.

Workshop | Systemische Therapie für Menschen mit sozialen Angststörungen (Hunger)

40 participants | Sunday, September 13th, 2020 | 9.30 - 13.00h

Soziale Angst, die schambesetzte intensive Furcht gegenüber anderen Personen, kann Menschen in die zwischenmenschliche Isolation führen; zumindest aber macht sie alle Kontakte mit anderen zu einer belastenden und kraftzehrenden Angelegenheit. Der Workshop beschreibt ein systemtherapeutisches Vorgehen, das in einem Pilotprojekt an der Universität Heidelberg entwickelt, in einem Manual präzisiert und dann in einer Vergleichsstudie gegenüber kognitiver Verhaltenstherapie überprüft wurde. Das Vorgehen kombiniert systemische Einzel-, Paar/Familien- und Gruppentherapie in einer Behandlung miteinander. Im Workshop können einzelne Bausteine aus dem Manual von den TeilnehmerInnen selbst erprobt und reflektiert werden. Ziele/Lernziele:
1) Vermittlung theoretischer Grundlagen rund um die Diagnose sozialer Angststörungen/Sozialphobie durch die Workshopleiterin, 2) Erproben und Reflektieren einzelner Interventionsmöglichkeiten in der Arbeit mit
Menschen mit ausgeprägten sozialen Ängsten.

Workshop | Estimating and interpreting psychological networks in R (Lange, Zickfeld)

Please bring your laptop - with R installed | 20 Participants | Sunday, September 13th, 2020 | 9.30 - 15.30h

Most research conceptualizes psychological constructs as unobservable (i.e., latent) entities that cause changes in measurable indicators. The indicators themselves have no direct causal effects on each other. For instance, depression can be conceptualized as a latent variable that causes changes in symptoms such as fatigue and concentration problems. From this perspective, fatigue and concentration problems do not have direct causal effects on each other. Alternatively, recent research on psychopathology, emotions, attitudes, beliefs, intelligence, or personality proposes to represent psychological constructs as networks of causal interactions between their components—the network approach. Specifically, depression may be a network of symptoms in which, among other things, fatigue causes concentration problems. To facilitate the
estimation of networks from data, multiple analytical techniques have been developed.
The goal of the workshop is to introduce (a) the theoretical framework of the network approach and (b) statistical network estimation and analysis tools. In the first part (approx. 30 minutes), we will discuss the theoretical foundation of the network approach in complexity science and its application to psychology. In the second part (approx. 180 minutes), we will showcase the estimation, visualization, and interpretation of two popular network models—the Ising model for binary data and the Gaussian Graphical Model for continuous data—in R. In the third part (approx. 90 minutes), attendees will analyze their own data or another data set that we will make available. Eventually, attendees will know about the theory and estimation of psychological networks.

Workshop | Desistance from crime - Empirische Befunde und ihre Implikationen für die Straffälligenhilfe (Beier, Oberlader)

30 participants (Minimum of 10 participants) | a fee applies (80,- Euro) | Sunday, September 13th, 2020 | 9.30 - 17.30h

Der Workshop vermittelt einen Überblick über wesentliche Erkenntnisse der Desistance-Forschung, die den Ausstiegsprozess aus kriminellen Karrieren untersucht (vgl. u.a. Maruna 2001). Aus diesen Inhalten werden praktische Implikationen für die Straffälligenhilfe beleuchtet.
Abschließend werden mit den Teilnehmer*innen Bezüge der Desistance-Forschung zum Risk-Need-Responsivity-Modell (u.a. Andrews & Bonta, 2010) und Good Lives Model (u.a. Ward, Mann, & Gannon, 2007; Ward & Gannon, 2006) diskutiert.

Workshop | Using reinforcement learning models in social neuroscience: A tutorial with hierarchical Bayesian approaches (Zhang, Lengersdorff, Hartmann)

40 participants | Sunday, September 13th, 2020 | 9.30 - 17.30h

Recent years have witnessed a dramatic increase in the use of reinforcement learning (RL) models in social, cognitive and affective neuroscience. This approach, in combination with neuroimaging techniques such as functional magnetic resonance imaging, enables quantitative investigations into latent mechanistic processes underlying social decision-making. Additionally, there is growing popularity of hierarchical Bayesian approaches for performing model estimation, which provides the granularity of population-level regulation meanwhile retains individual differences. However, cognitive and social neuroscientists do not necessarily have formal training in computational modeling, which involves multiple steps that require programming as well as quantitative skills. To bridge this gap, our tutorial will first we present a comprehensive framework for the examination of (social) decision-making with the simple Rescorla-Wagner RL model. We will then provide a principled interpretation of the functional role of the learning rate parameter. We will also discuss potential misconceptions of RL models and provide an applicable workflow for applying RL models. In the practical session, we will focus on a newly developed probabilistic programming language Stan (mc-stan.org), and an associated R package hBayesDM (github.com/CCS-Lab/hBayesDM) to perform hierarchical Bayesian analyses of a simple RL task. Lastly, we will showcase a few studies that applied RL models in social neuroscience. In sum, we aim to provide simple and scalable explanations and practical guidelines for employing RL models in order to assist both beginners and advanced users in better implementing and interpreting their model-based analyses.

Workshop | Modellierung von Forced-Choice Daten mit dem Thurstonian Item Response Modell in Mplus (Wetzel, Frick)

Please bring your laptop - with R and MPlus installed | 25 participants | Sunday, September 13th, 2020 | 9.30 - 17.30h

Im Forced-Choice Format müssen Testteilnehmende Items danach, wie gut sie sie beschreiben, in eine Rangfolge bringen oder diejenigen Items auswählen, die sie am besten und am schlechtesten beschreiben. Das Forced-Choice Format ist gegen Antwortstile wie Akquieszenz gefeit und weniger anfällig für Faking als Ratingskalen. Neue Entwicklungen wie das Thurstonian Item Response Modell (TIRT; Brown & Maydeu-Olivares, 2011) erlauben es, normative Traitschätzer aus Forced-Choice Daten zu gewinnen und ermöglichen damit den Einsatz von Forced-Choice Fragebögen in Selektionskontexten.
Das Ziel dieses Workshops ist es, Teilnehmerinnen und Teilnehmern zu vermitteln, wie man Forced-Choice Daten mit dem Thurstonian Item Response Modell in Mplus analysiert. Zu diesem Zweck werden wir zuerst
eine theoretische Einführung in das TIRT Modell geben. Dann werden wir eine Schritt-für-Schritt Anleitung liefern, wie man Daten aus Forced-Choice Fragebögen mit dem TIRT analysiert. Dies beinhaltet das
Rekodieren der Rohdaten in binäre Outcome-Variablen, die Modellspezifikation, die Modellschätzung sowie die Interpretation von Item- und Personenparametern. Die Teilnehmenden werden jeden dieser Schritte in praktischen Aufgaben anhand empirischer Daten unter Verwendung der Software R (Rekodierung) und Mplus (Modellspezifikation und Schätzung) üben können. Wir werden uns auf die Anwendung des TIRTs auf Persönlichkeitsitems, die als Triplets mit vollständigem Ranking präsentiert werden, konzentrieren, aber auch einige Beispiele für andere Varianten des Forced-Choice Formats zeigen. Wir werden zudem das Thema anschneiden, wie man mehrdimensionale Forced-Choice Fragebögen konstruiert.
Voraussetzungen: Die Teilnehmenden sollten mit Faktorenanalyse und Item Response Theorie vertraut sein. Die Teilnehmenden sollten etwas Erfahrung mit R und Mplus haben und ihre Laptops mit R und Mplus darauf installiert mitbringen.

Workshop | Wissenschaftskommunikation in der Psychologie – Ein In-Mind-Workshop (Crusius, Attig, König)

Please bring your laptop | 25 participants | Sunday, September 13th, 2020 | 9.30 - 19.30h

Psychologie zu vermitteln heißt, sie dahin zu bringen, wo sie zählt: Zu Leuten, die neugierig darauf sind, wie die Psyche funktioniert. Zu Menschen, die Entscheidungen treffen. Zu Euren Großeltern, die verstehen wollen, was Ihr eigentlich macht. Das ist lohnenswert, aber auch mit Herausforderungen verbunden. Wissenschaft hat ihre eigene Sprache, die nicht immer alltagstauglich ist. Unsere Methoden sind kompliziert und unsere Ergebnisse nicht immer eindeutig. Zudem kann es viel Aufwand erfordern, ein größeres Publikum zu erreichen.
Das In-Mind Magazin (de.in-mind.org) ist ein von Wissenschaftler*innen getragenes, ehrenamtliches Projekt, das direkte Wissenschaftskommunikation als Plattform und durch praktische Unterstützung möglich machen will. Die Dozent*innen des Workshops geben das Magazin heraus und sind als Autor*innen tätig. Sie sind überdies in der Vermittlung von psychologischer Wissenschaft in sozialen Medien und mit Podcasts tätig. Unsere Erfahrungen wollen wir in diesem Workshop weitergeben.
Wir werden uns mit verschiedenen Formen der Wissenschaftskommunikation beschäftigen und diese ausprobieren. Der Schwerpunkt wird auf dem populärwissenschaftlichen Schreiben liegen – in kürzester Form für Twitter & Co, in Blog-Beiträgen oder in längeren Magazin-Artikeln. Bitte bringt zum Workshop einen Entwurf für einen kurzen Blog-Artikel (ca. 300-600 Worte) mit. Ihr könnt ein spannendes psychologisches Phänomen darstellen, einen interessanten Befund erklären oder eine gesellschaftliche Debatte aus wissenschaftlicher Sicht beleuchten. Auf de.in-mind.org findet Ihr zur Orientierung Autor*innenhinweise zu diesem Format. Während des Workshops werden wir gemeinsam an Eurem Entwurf arbeiten. Unser Ziel ist, dass es am Ende des Workshops für jede*n Teilnehmer*in nicht mehr weit ist zu einem fertigen Text, den Ihr bei In-Mind einreichen könnt.

Workshop | An Introduction to Machine Learning in R (Sust, Schödel)

Please bring your laptop - with R installed | 30 participants | Sunday, September 13th, 2020 | 9.30 - 19.30h

Two different cultures can be distinguished in statistical modeling: A more traditional approach aims at describing data with stochastic models. This strategy puts an emphasis on the explanation of patterns in
the data and constitutes the current gold standard in psychological research. In contrast, the algorithmic modeling approach focusses on finding functions to predict outcomes with the highest accuracy possible. Psychological research has so far widely neglected this second approach. Lately however, the prediction of psychological and behavioral outcomes has gained increasing interest. Therefore, Yarkoni & Westfall
(2017) propose the application of machine learning methods. Contrary to the common belief that machine learning algorithms are black boxes, recent efforts in statistical science have improved the interpretability
of algorithmic models, which in turn yields new opportunities for application in psychological research.
In this workshop, we will introduce the basic concepts and ideas of machine learning (e.g., bias-variance trade-off, overfitting, resampling techniques, performance evaluation, and variable selection). Participants will be introduced to the random forest, a nonlinear machine learning algorithm that is known for its high predictive performance in many application settings. To demonstrate the strengths of the random forest method, we will compare its performance to linear regression models in a series of benchmark experiments. Finally, participants will learn some simple interpretation methods to take a look inside the black box models. The workshop consists of an alternation of theoretical introductions and practical examples in R. Afterwards, participants should be able to apply basic machine learning techniques to their own research.

Workshop | Hands-on browser-based experimentation with lab.js (Henninger)

Please bring your laptop | 25 participants | Sunday, September 13th, 2020 | 9.30 - 19.30h

Online experimentation promises more efficient research through access to larger, more diverse samples, as well as well as the opportunity to target specific populations of interest. However, even in the laboratory, browsers are a powerful, versatile tool for data collection. While survey research has long been conducted online, only recently have the tools emerged to build experimental studies for the browser easily.
This workshop provides a practical, non-technical introduction to browser-based experimentation with lab.js, a free, open-source experiment builder that offers an easy-to-use graphical user interface. Over the course of the day, we will go through all the necessary steps to design, construct and publish an online experiment, and discuss related issues such as best practices, ensuring data quality, and timing performance along the way. The goal is to empower researchers to build their own studies for both online and in-laboratory use. Our workshop assumes general familiarity with experimental designs and software, but does not require any specific prior technical knowledge. As we will be building studies together, we ask participants to bring a laptop of their own, and to have a recent browser installed.

Workshop | Smartphone Sensing in Psychological Science (Stachl, Harari)

Please bring your laptop - with R installed | 25 participants | Sunday, September 13th, 2020 | 9.30 - 19.30h

Smartphones are sensor-rich, computationally powerful, and near constant companions to their owners, providing research psychologists with unparalleled access to people’s behaviors and contexts as they unfold in
their everyday lives. Moreover, smartphones can query people about their subjective psychological states (via notifications to respond to survey questions). These features are paving the way for the use of smartphones
as data-collection tools in psychological research. In this workshop, we will: (1) provide an overview of smartphone sensing methods, highlighting the breadth of behavior and contextual information that is possible, (2) discuss the practical and technical and privacy considerations necessary for designing smartphone-sensing studies, and (3) review some of the analytic techniques that can be used to examine sensor-based behavioral patterns over time, (4) give a hands-on introduction to some of these methods using sensing data from some of our studies (e.g., psychometrics, predictive modeling).

Workshop | Big Data in der Psychologie (Nestler, Scharf)

30 participants | Sunday, September 13th, 2020 | 9.30 - 17.30h

Die zunehmende Digitalisierung unserer Lebensbereiche führt dazu, dass täglich unzählige Daten einzelner Personen oder Personengruppenentstehen. Mit Hilfe geeigneter statistischer Methoden können solch große Datenbestände dazu genutzt werden, psychologische Hypothesen zuprüfen und neue Hypothesen zu entwickeln. Der Workshop soll eine Einführung in Big Data-Techniken geben und so die Teilnehmer/innen in die Lage versetzen, große Datensätze für ihre Arbeit zu nutzen. Konkret werden wir im Workshop die folgenden Verfahren behandeln: Regularisierungsmethoden für Regressionsmodelle (Lasso- und Ridge-Regression), Entscheidungsbäume und Random Forests und Support Vector Machines. Alle Verfahren werden theoretisch eingeführt und dann wird gezeigt, wie man die Verfahren in der Statistik-Software R umsetzen kann.

Workshop | Psychology of Forced Migration – Exchange between Theory and Practice (Landmann, Winter, Niester, Kayser)

30 participants | Sunday, September 13th, 2020 | 14.00 - 19.30h

Forced migration has become a relevant societal topic in recent yearsand gained a considerable amount of attention in the social scientific field. Pressing questions that arise in this context are how service providers in the sector of education and the labor market as well as volunteers can be supported and how experiences of racism and discrimination can be discerned. The social psychological network on forced migration and integration seeks to develop different ways to respond to these questions (www.fachnetzflucht.de). In its approach to combine evidence provided bytheory and practice it seeks to establish a better exchange between science and practitioners in the field of refugee integration. With the intention to involve as many actors from public life as possible, it explicitly also invites individuals who experienced forced migration to participate in this dialogue. The workshop plan is to discuss recent projects, to evaluate completed projects and to plan future projects of the social psychological network on forced migration and integration. Among other things, the tasks and challenges we will address, are how we can evaluate the effectiveness of our projects, which further questions should be addressed on our website and how interested researchers, who are not part of the network yet, can write a contribution for the network. Interested parties from all disciplines are very welcome to participate in the workshop, to find out about the network via introductory speeches and to get involved in our work.

Workshop | Open Science for PIs: Etablierung transparenter Forschungsprinzipien in der eigenen Arbeitsgruppe (Fiebach, Gollwitzer, Abele-Brehm)

20 participants | a fee applies (50,- Euro) | Sunday, September 13th, 2020 | 14.00 - 19.30h

Eine größere Transparenz in der Forschung wird heutzutage von vielen Seiten erwartet, etwa von Förderorganisationen und Journals, aber auch von Nachwuchswissenschaftler/innen. Die Open Science-Bewegung zeigt Ansätze auf, diesen zentralen Wert der Wissenschaft zu realisieren und den Forschungsprozess offener zu gestalten. Gleichzeitig bietet sie aber auch Wege, die eigenen Arbeitsprozesse effizienter und robuster zu gestalten. Allerdings ist die Umsetzung von Open Science-Prinzipien in der eigenen Forschung und in der eigenen Arbeitsgruppe nicht immer einfach: Rechtliche Unklarheiten, zeitlicher Druck, aber auch fehlendes Wissen oder Interesse können Barrieren bei der Umsetzung darstellen. Dieser Workshop richtet sich gezielt an Arbeitsgruppenleiterinnen und-leiter (Principal Investigators) aller Karrierestufen, die die Implementierung von Open Science-Prinzipien in ihrer eigenen Forschungsarbeit bzw. ihrer Arbeitsgruppe anstreben. Im ersten Teil des Workshops werden Präregistrierung von Studien und Forschungsdatenmanagement als zentrale Komponenten transparenter Forschung komprimiert eingeführt (ca. 1,5 Stunden). Im zweiten Teil des Workshops berichten Kolleginnen und Kollegen im Rahmen von kurzen Impulsvorträgen über ihre praktischen Erfahrungen bei der Umsetzung von Open Science im eigenen Forschungsprozess. Vor diesem Hintergrund werden im Rahmen einer gemeinsamen Diskussionsrunde mögliche Probleme und Herausforderungen, die die Teilnehmerinnen und Teilnehmer identifizieren, diskutiert. Abschließend besteht die Möglichkeit, mit den neuen Erkenntnissen einen Aktionsplan für die eigene Arbeitsgruppezu entwerfen.

Workshop | Geographic Analysis for Psychologists (Ebert, Götz)

Please bring your laptop - with R or Stata installed | 30 participants | Sunday, September 13th, 2020 | 16.00 - 19.30h

Recent years have witnessed a strong upsurge in the interest of psychologists to examine geographical variation of psychological phenomena. In the digital age, large-scale psychological data allow researchers to analyse such geographical differences at an unprecedented scale. While spatial data create many fascinating research opportunities, working with spatial data involves unique methodological challenges. Overcoming these challenges requires methodological tools that are not part of the typical psychologist's toolkit. This workshop is designed to offer an accessible, hands-on introduction for psychologists to work with spatial data. Based on live demonstrations of methods and applications, we reproduce the entire research cycle from data acquisition to completed analysis. Thereby, we walk attendees through a do-it-yourself workshop that covers the following contents: (1) where to get psychological data suitable for geographical analyses, (2) how to geographically aggregate individual-level data, (3) how to create maps to visualize the spatial distribution of psychological phenomena, (4) how to create spatial-weight matrices and use them to assess geographical clustering,(5) how to use spatial regression models that account for the methodological challenges when regressing spatial data. The workshop is explicitly geared towards beginners. As such, it hopes to attract researchers from all psychological sub-disciplines who have been thinking about incorporating spatial data and methods into their research. No prior knowledge on spatial data or methods is needed, but some experience in either R or Stata is beneficial.

Workshop | How to deal with non-significant p-values and make them informative (Edelsbrunner, Thurn)

Please bring your laptop - with R, TOSTER and ggplot2 packages installed | 25 participants | Sunday, September 13th, 2020 | 16.00 - 19.30h

Reviews have shown that non-significant p-values are frequently misinterpreted as indicating evidence for the absence of an effect, or as indicating evidence for the difference to another effect that has turned out significant. In addition, non-significant p-values can tempt researchers to conduct further analyses and report only those providing significance, which biases the evidential value of individual and collective p-values. In this workshop, we start with half an hour of explanations and simulations which we conduct and interpret together in the free R software environment that will show us what a non-significant p-value really indicates, and what not. Based on these insights, we will discuss and practice the application of equivalence testing, a simple technique that can help us find out what a non-significant p-value really indicates. With this approach, one can differentiate whether a non-significant p-value really indicates evidence for the absence or negligible size of an effect, or whether the evidence is inconclusive. In another small group task, we will practice how we can determine a smallest effect size of interest, which is required for such approaches. Bayes factors will be introduced as another useful approach, and both approaches compared from the perspectives of multiple fields within psychology and methodological schools. About half of the participants (working in pairs or small groups will be fine) should have a mobile device with the R software environment and the TOSTER and ggplot2 packages installed, perhaps one of their own datasets prepared for R, and preferably a wifi connection.