A custom R function to create ggplot2 visualizations of fixed effects from models refitted with multiple optimizers using lme4's allFit function, enabling visual assessment of convergence validity in mixed-effects models.
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).
Covariates serve two essential purposes: statistically accounting for satellite variables that may affect variables of interest, and academically preventing the development of redundant theories by enabling direct comparisons between related theoretical constructs.
I would like to ask for advice regarding some plots that were created using brms::mcmc_plot(), and cannot be opened in R now. The plots were created last year using brms 2.17.0, and were saved in RDS objects. The problem I have is that I cannot open the plots in R now because I get an error related to a missing function. I would be very grateful if someone could please advise me if they can think of a possible reason or solution.
Here I share the format applied to tables presenting the results of Bayesian models in Bernabeu (2022). The sample table presents a mixed-effects model that was fitted using the R package ‘brms’ (Bürkner et al., 2022).
Here I share the format applied to tables presenting the results of frequentist models in Bernabeu (2022). The sample table presents a mixed-effects model that was fitted using the R package ‘lmerTest’ (Kuznetsova et al., 2022).
Custom function extending sjPlot that plots interactions between continuous and categorical variables while replacing categorical variables with alias variables to facilitate back-transformation of sum-coded predictors for clearer result communication.
Custom functions extending sjPlot for plotting interactions between two continuous variables by dividing one into ten bins (deciles) or six bins (sextiles), with optional sample size display in legend for individual differences research.
Frequentist and Bayesian statistics are sometimes regarded as fundamentally different philosophies. Indeed, can both qualify as philosophies or is one of them just a pointless ritual? Is frequentist statistics only about p values? Are frequentist estimates diametrically opposed to Bayesian posterior distributions? Are confidence intervals and credible intervals irreconcilable? Will R crash if lmerTest and brms are simultaneously loaded?
The first study (Bernabeu et al., 2021) will merge existing datasets (Lynott et al., 2020; Pexman et al., 2017; Pexman & Yap, 2018; Wingfield & Connell, 2019). The second study will collect novel data to investigate questions such as the unique roles of vocabulary size, sensorimotor experience and attentional control.
Critical examination of Liu et al. (2018) claims about methodological inconsistencies in ERP studies of conceptual modality switching, arguing that their conclusions overlook theoretical and methodological justifications for varying analytical approaches.
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.
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).
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 (https://github.com/pablobernabeu/Experimental-data-simulation).
Open-source, R-based web application for creating experimental data sets with customisable structures, including between-group and within-participant variables that can be categorical or continuous.
This project offers free activities to learn and practise reproducible data presentation. Pablo Bernabeu organises these events in the context of a Software Sustainability Institute Fellowship. Programming languages such as R and Python offer free, powerful resources for data processing, visualisation and analysis. Experience in these programs is highly valued in data-intensive disciplines. Original data has become a public good in many research fields thanks to cultural and technological advances. On the internet, we can find innumerable data sets from sources such as scientific journals and repositories (e.g., OSF), local and national governments, non-governmental organisations (e.g., data.world), etc. Activities comprise free workshops and datathons.
Overview of event-related potentials as a research method, covering electroencephalography fundamentals, ERP definitions and processing, and their application to studying the time course of cognitive processes like conceptual processing.
This app presents linguistic data over several tabs. It combines the R Markdown-based user interface of Flexdashboard with a Shiny back-end that lets users download the data they select as CSV files and the plots as PNG images. One of the hardest nuts to crack was changing the orientation of rows and columns without breaking the reactable tables. Flexdashboard also made it possible to use quite different formats in different tabs.
Part of the toolkit of language researchers is formed of stimuli that have been rated on various dimensions. The current study presents modality exclusivity norms for 336 properties and 411 concepts in Dutch. Forty-two respondents rated the auditory, …