research and teaching applications

Mixed-effects models in R, and a new tool for data simulation

Abstract Linear mixed-effects models (LMEMs) are used to account for variation within factors with multiple observations, such as participants, trials, items, channels, etc (for an earlier approach, see Clark, 1973). This variation is modelled in terms of random intercepts (e.g., overall variation per participant) as well as random slopes for the fixed effects (e.g., treatment effect per participant). These measures help reduce false positives and false negatives (Barr, Levy, Scheepers, & Tily, 2013), and the resulting models tend to be robust to violations of assumptions (Schielzeth et al.

Reproducibilidad en torno a una aplicación web

Las aplicaciones web nos ayudan a facilitar el uso de nuestro trabajo, ya que no requieren programación para utilizarlas. Crear estas aplicaciones en R, mediante paquetes como "shiny" o "flexdashboard", ofrece múltiples ventajas. Entre ellas destaca la reproducibilidad, tal como veremos en torno a una aplicación para la simulación de datos (

Stray meetings in Microsoft Teams

Unwanted, stranded meetings, overlapping with a general one in a channel, can occur when people click on the Meet (now)/📷 button, instead of clicking on the same Join button in the chat field. This may especially happen to those who reach the channel first, or who cannot see the Join button in the chat field because this field has been taken up by messages.

Web application for the simulation of experimental data

This open-source, R-based web application is suitable for educational or research purposes in experimental sciences. It allows the **creation of varied data sets with specified structures, such as between-group or within-participant variables, that …