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Julia Leesch
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Claudia O'Donovan-Bellante
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Open Science: Preregistration

Tobias Heycke

Date: 25.11 - 26.11.2019 ics-file

Location: Mannheim B2,8 / Course language: English

About the lecturer - Tobias Heycke

Course description

Recently, in empirical research two phenomenon have received a substantial amount of attention: p-hacking and HARKing. When running multiple analyses on the same data set and adjusting the analysis until a p-value smaller than the set alpha level is reached, we speak of p-hacking. This behavior is problematic as it (highly) increases the chance of an alpha error (Simmons, Nelson, & Simonsohn, 2011). HARKing (hypothesizing after the results are known) describes the behavior of researchers to present post-hoc hypotheses (usually based on statistically significant results) as a priori hypotheses (Kerr, 1998). Both p-hacking and HARKing can be dismissed, when the hypotheses and data analysis were preregistered before the data was collected (e.g., registration of clinical trials or experimental psychology studies).
One way to ensure we are neither p-hacking nor HARKing is to preregister our analysis plan. In this workshop we will discuss the need for preregistration, the difference between preregistration and registered reports and most importantly, we will take a look a preregistration forms for primary and secondary data analyses. Finally, we will work on individual preregistrations of our own research projects.


Target group

Everybody who is planning to conduct a study and run confirmatory analyses.

Learning objectives

The goal of this workshop is to (I) understand the need for preregistration, (II) understand different ways of preregistration, and (III) be aware of do's and don'ts in preregistration. Participants will work on a preregistration of their own work on the second day.


No prior knowledge of preregistration is required. Participants should have individual research ideas to work on their own preregistrations.


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