linear mixed-effects models

A new function to plot convergence diagnostics from lme4::allFit()

When a model has struggled to find enough information in the data to account for every predictor---especially for every random effect---, convergence warnings appear (Brauer & Curtin, 2018; Singmann & Kellen, 2019). In this article, I review the issue of convergence before presenting a new plotting function in R that facilitates the visualisation of the fixed effects fitted by different optimization algorithms (also dubbed optimizers).

Preregistration: The interplay between linguistic and embodied systems in conceptual processing

This preregistration outlines a study that will investigate the dynamic nature of conceptual processing by examining the interplay between linguistic distributional systems—comprising word co-occurrence and word association—and embodied systems—comprising sensorimotor and emotional information. A set of confirmatory research questions are addressed using data from the Calgary Semantic Decision project, along with additional measures for the stimuli corresponding to distributional language statistics, embodied information, and individual differences in vocabulary size.

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

In this talk, I will look over the rationale for LMEMs, and demonstrate how to fit them in R (Brauer & Curtin, 2018; Luke, 2017). Challenges will also be covered. For instance, when using the widely-accepted 'maximal' approach, based on fitting all possible random effects for each fixed effect, models sometimes fail to find a solution, or 'convergence'. Advice for the problem of nonconvergence will be demonstrated, based on the progressive lightening of the random effects structure (Singman & Kellen, 2017; for an alternative approach, especially with small samples, see Matuschek et al., 2017). At the end, on a different note, I will present a web application that facilitates data simulation for research and teaching (Bernabeu & Lynott, 2020).

Event-related potentials: Why and how I used them

Event-related potentials (ERPs) offer a unique insight in the study of human cognition. Let's look at their reason-to-be for the purposes of research, and how they are defined and processed. Most of this content is based on my master's thesis, which I could fortunately conduct at the Max Planck Institute for Psycholinguistics (see thesis or conference paper). Electroencephalography The brain produces electrical activity all the time, which can be measured via electrodes on the scalp—a method known as electroencephalography (EEG).

Modality switch effects emerge early and increase throughout conceptual processing: Evidence from ERPs

We tested whether conceptual processing is modality-specific by tracking the time course of the Conceptual Modality Switch effect. Forty-six participants verified the relation between property words and concept words. The conceptual modality of …

Modality switches occur early and extend late in conceptual processing: Evidence from ERPs [Master's thesis]

The engagement of sensory brain regions during word recognition is widely documented, yet its precise relevance is less clear. It would constitute perceptual simulation only if it has a functional role in conceptual processing. We investigated this …

Modality switch effects emerge early and increase throughout conceptual processing: Evidence from ERPs

Research has extensively investigated whether conceptual processing is modality-specific—that is, whether meaning is processed to a large extent on the basis of perceptual and motor affordances (Barsalou, 2016). This possibility challenges long-established theories. It suggests a strong link between physical experience and language which is not borne out of the paradigmatic arbitrariness of words (see Lockwood, Dingemanse, & Hagoort, 2016). Modality-specificity also clashes with models of language that have no link to sensory and motor systems (Barsalou, 2016).