Running on-line studies is one efficient way to run studies with absolute social distancing, however, not everybody knows how do this (yet). During this tutorial you will hear how to set up and run studies on-line. Bastiaan Rutjens will talk about the practicalities and pitfalls of running studies on-line, and will discuss different platforms to recruit participants and to make sure that you gather high-quality data.
For those who want to move their experimentation online, NeuroTask Scripting is a good option to consider. Jaap Murre will give a brief demo of some of the possibilities.
The aim is that the tutorial is accessible for people who have never done an on-line study, but also for people who can share their experience. Besides the speakers, several experienced on-line researchers and the people from the TOP will also be available to answer questions.
“Conducting research online using US and UK data markets”
In the last 2-3 years I have almost exclusively conducted my research online. Online research works well for correlational work, simple experiments, as well as various types of longitudinal design. There are various online platforms where researchers can crowdsource participants for their research. We will talk about our experiences with Amazon’s Mechanical Turk (US) and Prolific Academic (UK), focusing on participant selection, population demographics, instruction and attention checks, and data quality (e.g., compared to student samples).
For those who want to move their experimentation online, NeuroTask Scripting is a good option to consider.
In this Psych Forum we will have two excellent speakers that will provide a network perspective on the psychometrics and the brain.
In this talk I will introduce "network psychometrics" - an increasingly popular field of methods pioneered at the Psychological Methods program group aiming to map out the complex interplay between observed variables. I will present the theoretical foundations for network psychometrics show how such an analysis can be performed in R and discuss future directions in this area of research.
Many researchers are aware of the many benefits it can have to switch from classical statistics to Bayesian. And yet, almost as many are hesitant to do the switch, and all because of the priors! In Bayesian analysis, researchers must make a priori commitments, and these commitments are made transparently as part of model specification.
During this Psychological Forum you will learn about several ways to specify these a priori commitments. In the first talk, Julia Haaf will give an introduction to prior specification and the sometimes complicated terminology used around it. We will show which priors are appropriate for Bayesian estimation or Bayesian model comparison, and explain what a sensitivity analysis is.
In the second talk, Angelika Stefan will discuss different approaches that can be used to formulate priors based on existing pre-data knowledge. Specifically, we will show how results from the scientific literature, theoretical convictions, and domain expert knowledge can shape prior distributions. We will present several concrete examples, and discuss how the formulation of the prior distribution influences the results of Bayesian analyses. There will be lots of time for discussion and to ask questions. Share your favorite priors, or discuss analysis problems where you did not know which priors to chose.