Planning, analyzing, and sharing quantitative research (online)
Overview
Duration: 75 min
Questions
What transparency points to think about when planning an experiment?
How to organize and share research materials?
How to make decisions about statistical procedures?
How to establish transparency in data analysis?
What are points pertaining to transparency in frequentist statistics?
Planning involves deciding on the type of research questions, choosing variables to study, defning which variables and how they will be measured, and deciding on how many participants to recruit. Such decisions afect how to collect and analyze data. Ambiguities in describing the plan impede attempts to verify, replicate, and build upon the fndings.
This section will introduce the participants to lists of research decisions. We will show examples of how these decisions could infuence data analysis. We will discuss what information are necessary to preregister and why they matter. We will discuss types of research artifacts and how to share them according to the FAIR principles (Findability, Accessibility, Interoperability, and Reuse).
We will demonstrate and discuss analytic decisions in a statistical analysis example and discuss their implications from the perspective of transparency. This example will focus on frequentist statistics. (Bayesian statistics will be covered in lecture 2.)