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

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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).

Assigning participant-specific parameters automatically in OpenSesame

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OpenSesame offers options to counterbalance properties of the stimulus across participants. However, in cases of more involved assignments of session parameters across participants, it becomes necessary to write a bit of Python code in an inline script, which should be placed at the top of the timeline. In such a script, the participant-specific parameters are loaded in from a csv file. Below is a minimal example of the csv file.

Pronominal object clitics in preverbal position are a hard nut to crack for Google Translate

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Unlike English, some Romance languages not only allow—but sometimes require—pronominal object clitics in preverbal position (Hanson & Carlson, 2014; Labotka et al., 2023). That is, instead of saying La maestra ha detto il nome (Italian) ‘The teacher has said the name’, Italian allows Il nome lo ha detto la maestra (literally, ‘The name it has said the teacher’), which could translate as ‘The name has been said by the teacher’, ‘The teacher has said the name’, or even ‘It is the teacher that has said the name’.

Specifying version number in OSF download links

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How to append version numbers to OSF download links using the '?version=X' parameter to document and preserve the exact versions of files used in research projects.

Covariates are necessary to validate the variables of interest and to prevent bogus theories

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The need for covariates—or nuisance variables—in statistical analyses is twofold. The first reason is purely statistical and the second reason is academic. First, the use of covariates is often necessary when the variable(s) of interest in a study may be connected to, and affected by, some satellite variables (Bottini et al., 2022; Elze et al., 2017; Sassenhagen & Alday, 2016). This complex scenario is the most common one due to the multivariate, dynamic, interactive nature of the real world.

Cannot open plots created with brms::mcmc_plot due to lack of discrete_range function

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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.

A table of results for Bayesian mixed-effects models: Grouping variables and specifying random slopes

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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).

A table of results for frequentist mixed-effects models: Grouping variables and specifying random slopes

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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).

Plotting two-way interactions from mixed-effects models using alias variables

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Whereas the direction of main effects can be interpreted from the sign of the estimate, the interpretation of interaction effects often requires plots. This task is facilitated by the R package sjPlot (Lüdecke, 2022). In Bernabeu (2022), the sjPlot function called plot_model served as the basis for the creation of some custom functions. One of these functions is alias_interaction_plot, which allows the plotting of interactions between a continuous variable and a categorical variable.

Plotting two-way interactions from mixed-effects models using ten or six bins

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Whereas the direction of main effects can be interpreted from the sign of the estimate, the interpretation of interaction effects often requires plots. This task is facilitated by the R package sjPlot (Lüdecke, 2022). In Bernabeu (2022), the sjPlot function called plot_model served as the basis for the creation of some custom functions. Two of these functions are deciles_interaction_plot and sextiles_interaction_plot. These functions allow the plotting of interactions between two continuous variables.