Call for papers – SPUDM 26 – Technion, Israel

The European Association for Decision Making invites submissions for presentations, posters and/or symposia for its 2017 Biennial SPUDM 26 conference to be held at the Technion – the Israel Institute of Technology in Haifa, Israel, from Sunday August 20 to Thursday August 24, 2017.

All submissions must be made electronically.

Invited keynote speakers:
Alvin E. Roth, Stanford University, USA
Debora Estrin, Cornell Tech, USA
Ido Erev, Technion, Israel
Presidential Address by EADM president:
Andreas Glöckner, Göttingen University, Germany

The conference focus will combine traditional topics as well as new directions in Judgment and Decision Making research.

More details and submission guidelines are available on the conference website — https://spudm2017.net.technion.ac.il/call-for-papers/

For further assistance please contact the organizing committee at spudm26@idc.ac.il

We are looking forward to welcoming you in Haifa.

SPUDM 26 organizing committee:

Shahar Ayal, IDC Herzelia
David Budescu, Fordham University
Ido Erev, Technion – Israel Institute of Technology
Andreas Glöckner, Göttingen University
Ilana Ritov, Hebrew University
Shaul Shalvi, University of Amsterdam
Richárd Szántó, Corvinus University of Budapest

3rd EADM JDM Summer School

The European Association for Decision Making (EADM) is pleased to announce its third Judgment and Decision Making (JDM) Summer School for PhD Students. It will take place between 11-16 July 2016 at the University of Amsterdam, The Netherlands.

The Summer School will consist of a weeklong program of courses covering issues of methodology in Judgment and Decision Making (JDM) research including theory building (Martijn van Zomeren, Groningen), cognitive modeling (Ido Erev, Technion), open science (Daniel Lakens, Eindhoven; Susann Fiedler, MPI Bonn), panel data analysis (Andreas Glöckner and Marc Jekel, Hagen), games (Ori Weisel, Nottingham; Shaul Shalvi, Amsterdam), and process tracing (Michael Schulte-Mecklenbeck, Bern; Martijn Willemsen, Eindhoven).

EADM Summer School 2016 Program

If you ever wondered about EADM’s mission

The purpose of the Association is the advancement and diffusion of knowledge about human judgement and decision making and providing support for the exchange of information relating to this subject between the members and other associations throughout the world, as well as between members and other interested institutions and/or individuals. The Association is a non-profit organisation made up of interested researchers.

The Association aims to reach the goals mentioned above by:

  • the organisation and/or facilitation of meetings, workshops, summer-schools and conferences.
  • the promotion of scientific communication and research collaboration between members and between members and other scientists, policy makers, practitioners, and stakeholders.
  • the promotion of all (lawful) activities among members to help advise non-members (institutions and individuals) in accordance with the main goals of the Association.
  • co-operation with other associations and institutions within and outside Europe.

The specific activities of the EADM are:

  • the organisation of biannual conferences on Subjective Probability, Utility and Decision Making (SPUDM).
  • sponsoring the de Finetti Prize for promising PhD students.
  • sponsoring the Jane Beattie mid-career award in recognition of “innovation in decision research”, as broadly understood.
  • sponsoring the Wagenaar Award for travel to SPUDM
  • sponsoring the EADM/SJDM Jane Beattie travel award for travel to the SJDM annual conference.
  • supporting small-scale workshops.
  • organizing a bi-annual Summer-school on judgment and decision-making.
  • maintaining an electronic mailing list for EADM members.
  • maintaining a website featuring news and information for members and non-members
  • supporting the open access scientific journal Judgment and Decision Making, the journal of the Society for Judgment and Decision Making (SJDM) and the European Association for Decision Making (EADM).

The EADM Interview: Dirk Wulff

Dirk_Wulff2

1) Who are you, and what do you do?

My name is Dirk Wulff. I am a PostDoc at the Center for Adaptive Rationality at the Max Planck Institute of Human Development. I study experience-based decision making and semantic memory.

Within experienced-based decision making I focus quite a bit on exploration and information search. One aspect I am currently interested in is the impact of different stopping rules on the experiences that we make. We all know the problem of assessing the result of an experiment sample-by-sample. The same problem pertains to experience-based decision making. When we explore multiple options before making a choice, a stopping rule that is based on the perceived difference between the options will make the option appear more distinct then they actually are. What we experience can thus be influenced by what we wanted to experience.

Although I work mainly on decision making, I originally moved into research for my fascination with the study of semantic memory. Therefore, I feel lucky to be collaborating on a number of projects on the organization of semantic memory across the lifespan. One project that I find particularly cool is smallworldofwords.com. In this project researchers from many countries work together to obtain human-generated semantic networks for all words in 8 different languages. I help running the German version.

2) What do you consider your most important research tool(s) on your computer?

Hands down R. You have a new idea and you don’t know how it pans out – simulate it with R. You have a theory and you don’t whether it fits the data – model it with R. You have a nice result and want to show it exactly as you want to – plot it with R (base, not ggplot2). Writing code may actually be my favorite part of doing research – I mean aside from getting up late and coffee breaks – and R is perfect for it. Some time ago I also started using Python for natural language processing. The syntax is much more simple and elegant. Everything around the language, e.g., packages or available IDEs, is however nowhere near the convenience of using R (and RStudio).

3) What do you consider your most important research tool(s) outside of your computer?

A café. For some reason my mind is clearest, when working in my favorite café surrounded by chatting strangers. I sometimes joke that this is, because it lets me feel that I have a live outside of academia. The more likely reason however is: there is no Internet.

4) What is your favorite tip for getting writing done?

Force yourself. Or have someone else force you. Still desperately looking for alternative solutions.

Dirk’s CV

Favorite publication

Wulff, D. U., Hills, T. T., & Hertwig, R. (2015). How short- and long-run aspirations impact search and choice in decisions from experience. Cognition, 144, 29-37.

The EADM Interview: Peter Wakker

photowakker

1) Who are you, and what do you do?

I am the grandson of
http://people.few.eur.nl/wakker/miscella/private/myphotos/myfamily/myroots.jpg

I will convert all of mankind, including all statisticians, to Bayesianism.
I will introduce the idea of conservation of influence.

2) What do you consider your most important research tool(s) on your computer?  Delete-key.

3) What do you consider your most important research tool(s) outside of your computer?
Paper-shredder.

4)  What is your favorite tip for getting writing done?
Do not force yourself to write; it will not work.
Only forbid yourself to do anything other than writing.

Peter’s CV

The best paper that I ever co-authored was
Abdellaoui, Mohammed & Peter P. Wakker (2005). The Likelihood Method for Decision under Uncertainty. Theory and Decision, 58, 3–76.

It is also my least-cited paper. Explanation (to console myself): In those days the journal printed half per page what other journals did.  In another journal the paper would have taken 37 pages not 74.  No-one prints 74 pages for one paper.

The EADM Interview: Bettina von Helversen

BettinavHelversen1)    Who are you, and what do you do?

I’m a researcher at Basel University working at the Center for Economic Psychology. I investigate the cognitive processes underlying judgments and decisions and how they are shaped by the characteristics of the task and the abilities of the decision maker. A large part of my work focuses on when people rely on rule- and exemplar-based processing in judgment and understanding the memory processes underlying these processes. One project I’m currently working on aims on trying to understand when memories about previously encountered instances are likely to influence the decision process and how this depends on affective experiences when encountering the exemplars. In addition I’m interested in how and when people search for information and how this in influenced by affect and stress.

2)    What do you consider your most important research tool(s) on your computer?

After reading that question I got curious which programs I’m actually using on a daily basis and I downloaded an app that allowed me to track the programs I’m using (TimeSink). A one week trial run suggested that I used the following programs in order of frequency: Firefox, Mail, Word, Powerpoint, Preview (a pdf viewer), Mendeley, Excel, Skype, SPSS and Matlab. Overall, that seems about right, although the order probably changes quite a bit with the projects I’m working on and the amount of teaching I’m preparing. Taking office for granted, I could not imagine doing research without Mendeley, Skype or Matlab anymore.

3)    What do you consider your most important research tool(s) outside of your computer?

Well there is of course the lab without which I would not have much data, but even more important are the people I work with (though they are no tools). For me research works best as a collaborative effort in a team of two to three people.

4)    What is your favorite tip for getting writing done?

I have to admit I’m struggling quite a bit with writing. To get writing done I need to find a day without meetings and preferably no evening plans that allow me an early escape.Additionally, I can recommend fast working coauthors. The knowledge that someone is waiting usually gets me to get my part done much faster and it works even better if the other person was really fast in doing their part.

Bettina’s webpage

Bettina’s favorite paper:

Scholz, A., von Helversen, B., & Rieskamp, J. (2015). Eye movements reveal memory-processes during similarity versus rule-based decision making. Cognition, 136,228-246. doi:10.1016/j.cognition.2014.11.019

The EADM Interview: Nathaniel Phillips

Nathaniel PhillipsWho are you, and what do you do?

My name is Nathaniel Phillips and I am a post-doctoral researcher at SPDS (Social Psychology and Decision Sciences) at the University of Konstanz in Germany. Thematically, I am interested in decisions under uncertainty, with a focus on information search, impression formation, and decision making. In other words, “How can organisms with limited time and cognitive limitations make good decisions in uncertain environments?” Methodologically, I try to use computational cognitive modelling, Bayesian graphical modelling, and agent-based simulations (I thank two summer schools, Lewandowsky and Farrell’s Computational Cognitive Modelling school and Wagenmakers and Lee’s Bayesian modelling school for introducing me to these techniques).

What do you consider your most important research tool(s) on your computer?

This is an easy one: Amazon mechanical turk (mTurk), and R (through RStudio). These two research tools completely changed how I envision psychological research. The mTurk allows virtually anyone (well, with an American bank account…) to obtain high quality data inexpensively from a highly diverse participant population. The mTurk has freed me from the physical and monetary demands of a computer lab, and has allowed me to program and conduct experiments in English while working in a non-English speaking city.

One note about the mTurk – some of my colleagues have wondered whether or not the low cost of mTurk data will lead to an explosion of a theoretical, p-hacked results. Indeed, if it only costs 5c per participant to collect data, why not run 64 conditions and only report the ones with significant results? Of course, p-hacking and the file-drawer problem existed long before the mTurk, but certainly the low cost of the mTurk makes this easier. However, mTurk p-hackers have a problem: anyone who questions the validity of their results can quickly and cheaply try to replicate the results using the exact same experimental materials on the exact same participant population. In short, if the original result was the result of a cheap mTurk p-hack, it can be rectified by an equally cheap mTurk replication.

The second most important research tool I have is R. Like most psychology students, my first stats courses used SPSS and I used SPSS through my Masters degree. At the beginning of my PhD, when I realised that all the senior researchers were using Matlab or R, I decided to make the switch to R (if for no other reason than to fit in). The first couple of months learning R were brutal – I went from feeling very comfortable with stats to a feeling like a complete beginner. That was definitely a hit to my ego, but after a few months of persistence and SPSS-reflex resistance, I made the complete switch and have been appreciating R more and more ever since.

There are just so many benefits to R and virtually no disadvantages (relative to SPSS, I’m sure some Python and Matlab users will find some drawbacks). R is free, constantly updated, allows you to make gorgeous plots, and is widely used by people working in all areas of research. However, I think the single best benefit of R is research transparency and replicability. Unlike SPSS analyses, R code can be easily stored and shared with others. If a colleague, or your notoriously forgetful future self wants to know how you conducted a certain analyses, just send them your code (properly commented of course).

I firmly believe that all undergraduate psychology students should be taught R from day-1 and should never be exposed to SPSS. So why aren’t we teaching students R? When I posed this question to one senior statistics instructor, he responded: “we can’t teach undergraduate students R because they won’t be able to or won’t want to use it.” Interesting … by the same argument, we should not teach statistics to psychology students.

I am confident that most students will learn how to conduct statistical analyses in R much faster than in SPSS. If a student can type “cor(x,y)” then she can calculate a correlation coefficient. If he can type “lm(y ~ x1 + x2 + x3)” he can conduct multiple regression. Bayesian stats? Not possible in SPSS and no problem in R, just type “BESTmcmc(x,y)” using Kruschke’s BEST R package and you’ve got a Bayesian “t-test” (see Kruschke, 2010). Additionally, because you can easily simulate data in R, you can easily program examples of important topics such as the central limit theorem and show students that it works.

Speaking of R, I recently started learning how to write in Latex using Sweave in RStudio and am kicking myself for not learning it earlier. For those who don’t know, Sweave is a way to incorporate R code into a Latex document. What’s really great about this setup is that it allows you embed your R analyses directly into your written document. For example, in Sweave you can write “The mean response time of distracted participants was \Sexpr{mean(response.time)}” where the result in \Sexpr{} is printed in plain text. The main benefit of Sweave is that it makes your analyses completely transparent to others, and your future self! If you use Sweave, you’ll never look back on an old document and wonder “How did I calculate that p-value?!” (not that you should be calculating p-values anyway…see Wagenmakers, 2007). You can always look at the Latex source code and see exactly where every analysis came from. For those that are interested in learning how to use Sweave, I recommend reading the short paper “Learning to Sweave in APA Style” by Ista Zahn

What do you consider your most important research tool(s) outside of your computer?

A moleskin journal and a mechanical pencil (with lots of erasers)

What is your favorite tip for getting writing done?

I think the best way to get writing done is to have firm deadlines and scheduled writing times. I learned these and many other great tips from Silviia’s book “How to Write a Lot

Nathaniel’s webpage

Nathaniel’s favorite paper:

Phillips, N.D., Hertwig, R., Kareev, Y. & Avrahami, J. (2014). Rivals in the dark: How competition influences search in decisions under uncertainty. Cognition, 133 (1), 104-119.

Workshop: Navigating Clinical Uncertainty

Navigating Clinical Uncertainty

10th European Workshop on Clinical Reasoning and Decision Making &

COGITA: Gut Feelings in General Practice

March 26th – March 28th , 2015

Marburg (Germany)

Dear colleagues,

we gladly announce the 10th workshop on Clinical Decision Making and Diagnostic Reasoning, this time in collaboration with the COGITA-group, a European network of researchers focusing on the role of gut feelings in the diagnostic reasoning of general practitioners. This conference will be hosted by the Departments of General Practice and Clinical Psychology at the University of Marburg (Germany). The aim of this interdisciplinary workshop is to bring together researchers from decision and clinical science as well as clinicians to share their ideas, their research and their experience. The workshop is sponsored by the European Association for Decision Making and attendance is free.

For more information see

http://www.uni-marburg.de/fb20/allgprmed/europeanworkshop

We are looking forward to seeing you all in Marburg!

 

The Scientific Committee:

Norbert Donner-Banzhoff (Marburg/D), Laurence Claes (Leuven/B), York Hagmayer (Göttingen/D), Erik Stolper (Maastricht/NL), Winfried Rief (Marburg/D), Cilia Witteman (Nijmegen/NL)