Ben Bolker's research while affiliated with McMaster University and other places

Publications (3)

Article
Full-text available
Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The for...

Citations

... 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. ...
... Daily movement-related variables (distance walked and vertical movement) were analysed with linear mixed effects models using the lmer function of the lme4 package (Bates et al. 2015). The models included the continuous linear effects of Julian date, distance walked in the morning, outdoor time, and (only for daily distance walked) daily vertical movement, the categorical effects of breed, rain occurrence and temperature class, and the random effect of individual cow. ...
... Eight of the haplotypes from Clarke et al. (2015) were shared between the Indo-Pacific clade, the Atlantic clade, and the market-derived samples (Figure 4(a)). Therefore, we used the haplotype frequencies from Clarke et al. (2015) and the frequencies of those haplotypes in the shark fin markets (Figure 4(a)) to conduct a mixed-stock analysis (MSA) with the R-package mixstock (Bolker, 2012). Mixstock was used to estimate the contribution of each source population (i.e., Indo-Pacific and Atlantic) to both shark fin markets using a Markov Chain Monte Carlo (MCMC) estimation with 100,000 iterations following a burn-in of 50,000. ...