Research is messy: Two cases of pre-registrations

Pre-registrations are becoming increasingly important for studies in psychological research. This is a much needed change since part of the “replication crisis” has to do with too much flexibility in data analysis and interpretation (p-hacking, HARK’ing and the like). Pre-registering a study with planned sample size and planned analyses allows other researchers to understand what the initial thinking of the authors was, how the data fits to the initial hypothesis and where are differences between the study protocol and study results. In theory, it looks very simple: you think about a problem, you conceive a study, lay out the plan, register it, collect data, analyse and publish.  Continue reading Research is messy: Two cases of pre-registrations

Replicability, Data Quality and Bayesian Methods

On the About page I wrote, that I blog about things I come across while researching for my PhD. So, you may very well ask what this PhD is supposed to be about. For the interested reader — researchers and the uninitiated alike —, here is some overview on my current plans and research focus.

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ASA statement on p-Values: Improving valid statistical reasoning

A lot of debate (and part of my thesis) revolve around replicability and the proper use of inferential methods. The American Statistical Association has now published a statement on the use and the interpretation of p-Values (freely available, yay). It includes six principles and how to handle p-Values. None of them are new in a theoretical sense. It is more a symbolic act to remind scientists to properly use and interpret p-values.

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