replication crisis

Communication journals that adopted open science principles

With more and more communication scholars adopting open science principles (e.g., preregistration, sharing of data, material, and code), also more and more media and communication journals adopt open science features and take first steps in adopting the TOP guidelines. I just quickly would like to point your attention to a very useful resource in this regard. Moritz Büchi and Tobias Dienlin started a list with peer-reviewed journals that a) focus on media and communication generally or… Read More »Communication journals that adopted open science principles

New Publication: An Agenda for Open Science in Communication

In the last 10 years, many canonical findings in the social sciences appear unreliable. This so-called “replication crisis” has spurred calls for open science practices, which aim to increase the reproducibility, replicability, and generalizability of findings. Communication research is subject to many of the same challenges that have caused low replicability in other fields. As a result, I recently wrote a paper with more than 30 authors in which we propose an agenda for adopting… Read More »New Publication: An Agenda for Open Science in Communication

Estimating power for structural equation models: Simulations in R

Computing a priori power analyses for simple statistical models can be done analytically (e.g., with G*Power or the pwr package in R). However, estimating the power for more complex models and in particular structural equation models (SEM) is not as straightforward and requires simulations. I recently came across the package paramtest (Hughes, 2017) which provides a great framework for conducting more complex power simulations. In what follows, I provide some examples of how to simulate… Read More »Estimating power for structural equation models: Simulations in R

How to do specification curve analyses in R: Introducing ‘specr’

In the last month, Michael Scharkow and I have worked on a new R-package called specr. The goal was to facilitate specification curve analyses (also called multiverse analyses). The idea behind a specification curve analysis stems from the observation that a researcher has many degrees of freedom when conducting a quantitative analysis of a data set and sometimes, we do not really know how different decisions may impact the results. It starts with the question… Read More »How to do specification curve analyses in R: Introducing ‘specr’