S. Walker's scientific contributions
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Publications (3)
Description Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' ``glue''.
Citations
... The first analysis employed four linear mixed-effects models in R (R Core Team, 2023) using the lme4 package (Bates et al., 2023). Normalized F1, F2, F3, and duration (ms) comprised the dependent variables. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/278742950793218-1443468906117_Q64/Douglas-Bates.jpg)
![[object Object]](https://i1.rgstatic.net/ii/profile.image/272419030040595-1441961166388_Q64/Martin-Maechler.jpg)
... The model results at the different test times were analysed using generalised linear mixed-effects regression models ("lme4" package in R, Bates et al., 2014). Models were constructed for null and overt pronouns separately, each time with interpretation (subject or non-subject) as the dependent variable, test time as a fixed factor, and intercepts for simulated participants as a random factor. ...
... The contribution of each independent variable was also calculated using a variance partitioning approach (Nakagawa and Schielzeth, 2013). Linear mixed-effects models were fitted using the R-package "lme4" (Bates et al., 2015). ...
