WORKSHOPS

The Workshops will take place at Universidad Europea de Madrid (campus Villaviciosa de Odón) the July 14th at 9:00. Shuttle service from partner hotels to the venue and vice versa will be available. The shuttle will pick up attendees at 8:30 from the hotels and will take them back at 13:00 from the university. Please note that a Workshop will only be given if a minimum of 15 people have registered for it. The maximum of attendees accepted in each Workshop will be 25.
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R Applied to Personality Research Workshop

Speakers:

Miguel A. Sorrel and Pablo Nájera / Departamento de Psicología Social y Metodología, Universidad Autónoma de Madrid

Objectives:

Psychological research often comprises the study of multiple variables, both observable and latent, with the aim of either understanding their relationships in pursuit of theory development, or predicting an outcome for applied purposes. A number of statistical software packages have been developed to facilitate these analyses. A problematic issue is that most of these software packages have at least one of the following drawbacks: they include a narrow range of statistical procedures which limits what researchers can do, or they are commercially distributed products and thus can be expensive. One of the most remarkable exceptions is R (R Core Team, 2019), a free, open-source software focused on statistical computing, that is becoming increasingly popular in psychology. Thus, the main objective of this workshop is that the participants learn how to conduct some of the most used analyses in psychometrics research, with a particular focus on personality, using RStudio (an integrated development environment for R; RStudio Team, 2018). The course will consist of three sections: (1) Classic psychometrics, involving a brief introduction to classical test theory and multiple linear regression; (2) Latent variable modeling, consisting of factor analysis and structural equation modeling techniques (e.g., Abad, Sorrel, Garcia, & Aluja, 2018); and (3) Growing areas of interest, which will discuss modern approaches such as item response theory, computerized adaptive testing, and briefly introduce some alternatives for the study of personality, such as cognitive diagnosis modeling (e.g., de la Torre, van der Ark, & Rossi, 2018; Nieto et al., 2017). The course is intended for applied researchers who are somehow already familiar with the analyses and want to learn how to conduct them in R. Every statistical procedure will be explained with the use of real data examples from personality inventories. By the end of the course, participants are expected to know how to apply each of the aforementioned analyses to their own research works using R.

Requirements:

  • Basic knowledge of classical test theory and factor analysis.
  • Basic data manipulation in R: entering, importing, and exporting data.
  • Experience conducting test validation research is advisable.

Short Workshop Program:

  1. Brief Introduction to R and RStudio.
  2. Classic Psychometrics: Classical test theory and multiple linear regression.
  3. Latent Variable Modeling: Factor analysis and structural equation modeling.
  4. Growing Areas of Interest: Item response theory, computerized adaptive testing, and cognitive diagnosis modeling.

Key references:

Abad, F. J., Sorrel, M. A., García, L. F., & Aluja, A. (2018). Modeling general, specific, and method variance in personality measures: Results for ZKA-PQ and NEO-PI-R. Assessment, 25(8), 959-977. doi:10.1177/1073191116667547

De la Torre, J., van der Ark, L. A., & Rossi, G. (2018). Analysis of clinical data from a cognitive diagnosis modeling framework. Measurement and Evaluation in Counseling and Development, 51(4), 281-296.

Nieto, M. D., Abad, F. J., Hernández-Camacho, A., Garrido, L. E., Barrada, J. R., Aguado, D., & Olea, J. (2017). Calibrating a new item pool to adaptively assess the Big Five. Psicothema, 29(3), 390-395. doi:10.7334/psicothema2016.391

R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL

R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/

RStudio Team (2018). RStudio: Integrated Development for R. RStudio, Inc., Boston, MA URL http://www.rstudio.com/

Taking some of the regret out of preregistration

Speakers:

Ruben Arslan, Max Planck Institute for Human Development, Berlin, Germany

Julia Stern, Department of Psychology & Leibniz ScienceCampus Primate Cognition, University of Goettingen, Germany

Objectives:

In this workshop, we aim to give you practical guidance on formulating and following preregistrations, advice on balancing priorities and on handling the inevitable unforeseen pitfalls and regrettable decisions. Preregistrations and registered reports can drastically reduce overfitting and other questionable research practices and hence improve the trustworthiness of your research. It is less commonly appreciated that they can help you make more principled decisions, and reduce the requested post-hoc work from advisors, co-authors, and reviewers. Still, they also offer a chance to get intimately acquainted with the planning fallacy. You will truly "appreciate" how much statistics knowledge you acquire over the course of your career only once you have regretted the decisions of that utter naïf, past you. Are registered reports superior to mere preregistration, because you get an outside reality check sooner and cannot write an ambitious yet unfinishable plan? Or is it wiser not to spend the time upfront in review? What can we do, when we inevitably regret some of our fixed decisions and how can robustness checks help? Which decisions should you really preregister and which matter less for overfitting concerns? What do you do when you have resolved to do something that you now know was truly wrong? We have been through it all. We will talk about our mistakes, lessons learnt, and why and when we still think it is great to preregister and submit registered reports.

Requirements:


Ideally, you are currently planning a study, writing a preregistration, or writing up a preregistered study. We will share R code examples with attendees, but it is not a necessary precondition to work with R.

Short Workshop Program:

1. Brief introduction to preregistration and registered reports
2. Discuss common decisions to be made in a preregistration and how to
strike a balance between excessive rigidity, potential for overfitting, and sheer length.
3. Compare templates for preregistration
4. How to deal with that naïve fool, past you.
5. Deviating from the preregistration, testing robustness, and reporting it all.

Social Desirability and Acquiescence Control

Speaker:

David Navarro-González / Technological Innovations in the measure of Latent Traits / Universitat Rovira i Virgili

Objectives:

The impact of response biases in psychological inventories is an issue that has generated a lot of controversy in recent decades. The literature has demonstrated that the presence of those biases in a questionnaire impacts the factor structure (Navarro-González, Lorenzo-Seva, & Vigil-Colet, 2016; Rammstedt, Goldberg, & Borg, 2010) and the validity (Ones, Dilchert, Viswesvaran, & Judge, 2007; Salgado, 2005) of the inventory, distorting the interpretation of both the participant’s scores and also the relationship with other variables. The main objective of this workshop is that the participants acquire knowledge about the impact of response biases like the Social Desirability and Acquiescence in typical response measures, and how to deal with them when developing a questionnaire. We are going to show a useful tool to deal with response biases during the construction of a questionnaire, called Psychological Test Toolbox (Navarro-González, Vigil-Colet, Ferrando, & Lorenzo-Seva, 2019), which is a free program designed to apply the response biases control method proposed by Ferrando, Lorenzo-Seva, and Chico (2009). We are also going to illustrate the usefulness of the method included in the program by using real data from OPERAS (Vigil-Colet, Morales-Vives, Camps, Tous, & Lorenzo-Seva, 2013), which is a five-factor personality inventory developed using the methodology previously described. In the final part of the workshop, we are going to analyze the data using the method proposed by Ferrando et al. (2009) and using a traditional Factor Analysis approach. When comparing the results, we are going to analyze the differential impact between both response biases in the factor structure of a personality inventory.

Requirements:

  • Basic knowledge of test construction process.
  • Experience applying Factor Analysis technique is advisable.

Short Workshop Program:

  1. Introduction to response biases (focusing on Social Desirability and Acquiescence) and his impact on typical response measures.
  2. How to control the impact of response biases when developing an inventory: existent alternatives and the method by Ferrando, et al. (2009).
  3. Psychological Test Toolbox: a software to perform Factor Analysis controlling response biases.
  4. An empirical example: OPERAS (Vigil-Colet et al., 2013), a five-factor personality questionnaire which allows scores free of Social Desirability and Acquiescence effects to be obtained.

Key references:

Ferrando, P. J., Lorenzo-Seva U., Chico E. (2009). A general factor-analytic procedure for assessing response bias in questionnaire Measures. Structural Equation Modeling, 16(2), 364-381. doi:10.1080/10705510902751374.

Navarro-González D., Lorenzo-Seva U., Vigil-Colet A. (2016). How response bias affects the factorial structure of personality self-reports. Psicothema, 28(4), 465-470. doi:10.7334/psicothema2016.113.

Navarro-González, D., Vigil-Colet, A., Ferrando, P. J., & Lorenzo-Seva, U. (2019). Psychological Test Toolbox: A new tool to compute Factor Analysis controlling response bias. Journal of Statistical Software, 91(6). doi:10.18637/jss.v091.i06

Vigil-Colet, A., Morales-Vives, F., Camps, E., Tous, J., & Lorenzo-Seva, U. (2013). Development and validation of the Overall Personality Assessment Scale (OPERAS). Psicothema, 25(1), 100-106. doi:10.7334/psicothema2011.411

Manage Balance between Work and Personal Life

Speaker:

Prof. Dr. Franciska Krings, University of Lausanne, Switzerland

Objectives:

Managing the balance between the various, sometimes conflicting demands coming from being engaged at work and in one’s personal life can be quite a challenge. Feeling out of balance or feeling that juggling the demands of the two domains is a “mission impossible” often leads to stress and fatigue. This workshop will address this issue first from a scientific point of view by highlighting what we know from research about work-life conflict. Further, it will help participants gain a better understanding of their own work-life (im)balances, and provide advice on how to manage them. Finally, it will provide insights on how to deal with co-workers or employees who experience higher levels of work-family conflict.

Short Workshop Program:

  • Input on work-life conflict and work-life enrichment, their antecedents and consequences: What do we know?
  • Exercises to gain a better understanding of one’s own work-life balance
  • Exercises and input on how to manage one’s own work-life conflicts and on how to deal with co-workers who experience work-life conflict

The registration system for the European Conference of Personality 2020 is open now!
You can register and/or submit your paper by creating your Conftool account.

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