The latest update of the DHARMa R package (0.4.6) includes an option to perform simulated likelihood ratio tests (LRTs) for GLMMs based on a parametric bootstrap. I wanted to shortly comment on how this works and why this is useful. Why is this useful? A well-known issue with mixed models is that the df lost…
Note also the blog post by Daniel Lakens on the same topic here. Update March 23, 2022: a more concise / slightly modified version of these thoughts was published as a letter in TREE, co-authored together with Fred Barraquand. Background Criticism of p-values has been rampant in recent years, as were predictions of their imminent…
In regression analysis, a common problem is to decide on the right functional form of the fitted model. On the one hand, we would like to make the model as flexible as possible so that it can adjust itself bias-free to the true data-generating process. On the other hand, the more freedom we give the…
Do you remember the notorious hurricane / himmicane study (Jung et al., PNAS, 2014)? At the time, there was a heavy backlash against the study, and probably rightly so, as the statistical analysis turns out to be highly unstable against a change of the regression formula. You can find some links here. Over the years,…
tl;dr: DHARMa tests will pick up on overdispersion before you see a rise of Type I error. Overdispersion is a common problem in GL(M)Ms with fixed dispersion, such as Poisson or binomial GLMs. Here an explanation from the DHARMa vignette: GL(M)Ms often display over/underdispersion, which means that residual variance is larger/smaller than expected under the…
A colleague forwarded me a preprint (Louca and Pennell, 2019), which questions if time-varying extinction / speciation rates can be simultaneously inferred from extant phylogenies. I’d like to preface this by saying that this is not really my core expertise, so take my points with a grain of salt. Anyway, I was interested in the…
Although one would think that the basic concepts of statistics should be the same across all sciences, there is an amazing heterogeneity between fields in how statistics is taught and practiced. One example are the validity concepts (e.g. construct validity, internal validity, external validity) that are heavily taught in the social sciences and economics (see…
Over at dynamic ecology, Jeremy Fox argues that Technical statistical mistakes are overrated; ecologists (especially students) worry too much about them. Individually and collectively, technical statistical mistakes hardly ever appreciably slow the progress of entire subfields or sub-subfields. And fixing them rarely meaningfully accelerates progress. continuing with Don’t agree? Try this exercise: name the most…
Originally posted on AK Computational Ecology:
This guest post by Carsten F. Dormann, with inputs from Casper Kraan and the panel (see below) summarises the results from the short workshop “Biotic interactions and joint species distribution models” at the Ecology Across Borders BES/GfÖ/NEVECOL/EEF-meeting 2017 in Ghent, Belgium. The purpose of this event was to exchange thoughts and…
This is a somewhat belated introduction of a package that we published on CRAN at the beginning of the year already, but I hadn’t found the time to blog about this earlier. In the R environment and beyond, a large number of packages exist that estimate posterior distributions via MCMC sampling, either for specific statistical models (e.g.…
In good old tradition, including being too late, I provide here the JCR 2016 data for the top 40 journals indexed by what is now Clarivate Analytics’ Web of Science in the subject area “Ecology”, released in June 2017 (see footnote 1). For comparison, see my old posts, summarizing the JCR 2015, JCR 2014, JCR 2013, JCR 2012, JCR…
As I said before, I firmly side with Andrew Gelman (see e.g. here) in that model checking is dangerously neglected in Bayesian practice. The philosophical criticism against “rejecting” models (double-using data etc. etc.) is all well, but when using Bayesian methods in practice, I see few sensible alternatives to residual checks (both guessing a model and…
We are pleased to announce our 7th international summer school on Bayesian Modelling in the ecological and environmental sciences (see past courses here). This year the course will take place at the Heathland Centre on the beautiful island of Lygra in western Norway. Motivation Bayesian inference is an increasingly used statistical framework in ecology and…
I just released a small R package that I have been working on for a while. The motivation for this package came from the observation that I kept on receiving questions about residual checks for GLMMs. The problem that people have is that they have fitted their GLMM, maybe they tested it for overdispersion and…
I am moving to a professorship at the University of Regensburg, and I am looking to fill a lecturer position (Akad. Rat a.Z.) for a quantitative ecologist (= some focus on theory, modeling or stats) in my new group. If the job ad below seems to fit for you, please do apply, and feel free…
As for the JCR 2014, JCR 2013, JCR 2012, JCR 2011 and JCR 2010, here the 40 most highly cited journals indexed by the ISI Web of Knowledge under the subject area “Ecology”. Rank ’15 Journal Publications IF’15 5-yr IF ’15 1 TRENDS IN ECOLOGY & EVOLUTION 72 16.74 19.42 2 ECOLOGY LETTERS 138 10.77 14.94…
As for JCR 2013, JCR 2012, JCR 2011 and JCR 2010, I list the 40 most highly cited journals indexed by the ISI Web of Knowledge under the subject “ecology”. To give you a reference to the general journals: Nature is now (last year) at 41.456 (42.351), Science at 31.477 (33.611), Plos Biology at 9.343…
For a few years now, Jörn Pagel, Joseph Chipperfield, Björn Reineking (in the beginning) and I have been teaching an introductory summer school in Bayesian statistics. In previous years, we were in Bayreuth 2011 Bayreuth 2012, Göttingen 2013, Freiburg 2013 and Bergen 2014. This year, we will be again in Lygra, a beautiful field station…
A guest post by Gita Benadi and Jochen Fründ Mutualistic networks have become an increasingly popular way of describing mutually beneficial interactions between species-rich communities, for example those between plants and their pollinators. Besides offering a nice method of visualizing these interactions, networks are also used to make inferences about the relationship between interaction structure…
The central quantity in Bayesian inference, the posterior, can usually not be calculated analytically, but needs to be estimated by numerical integration, which is typically done with a Monte-Carlo algorithm. The three main algorithm classes for doing so are Rejection sampling Markov-Chain Monte Carlo (MCMC) sampling Sequential Monte Carlo (SMC) sampling I have previously given…
theoretical ecology 