# Month: July 2011

### New R resource for ordinary and multilevel regression modeling

Here’ s what I received from the Center of Multilevel Modeling at Bristol (I haven’t checked it out yet; registration seems to be free but required):

The Centre for Multilevel Modelling is very pleased to announce the addition of R practicals to our free on-line multilevel modelling course. These give detailed instructions of how to carry out a range of analyses in R, starting from multiple regression and progressing through to multilevel modelling of continuous and binary data using the lmer and glmer functions. MLwiN and Stata versions of these practicals are already available. You will need to log on or register onto the course to view these practicals. Read More... http://www.cmm.bris.ac.uk/lemma/course/view.php?id=13

### LSA 2011 class on Computational Psycholinguistics

Due to popular demandðŸ˜‰ – you can find the *Computational Psycholinguistics *class Roger Levy and I are currently teaching at the LSA 2011 institute at Boulder mirrored here.

### R code for Jaeger, Graff, Croft and Pontillo (2011): Mixed effect models for genetic and areal dependencies in linguistic typology: Commentary on Atkinson

Below I am sharing the R code for our paper on the serial founder effect:

- Jaeger, Graff, Croft, and Pontillo. 2011. Mixed effect models for genetic and areal dependencies in linguistic typology: Commentary on Atkinson
*. Linguistic Typology 15(2), 281â€“319.*Â [if you’re not subscribed to Linguistic Typology, check out this pre-finalÂ draftÂ or contact me for an offprint].

This paper is a commentary onÂ Atkinson’s 2011 Science article on the serial founder modelÂ (see also thisÂ interview with ScienceNews, in which parts of our comment in Linguistic Typology and follow-up work are summarized). In the commentary, we provide an introduction to linear mixed effect models for typological research. We discuss how to fit and to evaluate these models, using Atkinson’s data as an example.We illustrate the use of crossed random effects to control for genetic and areal relations between languages. We also introduce a (novel?) way to model areal dependencies based on an exponential decay function over migration distances between languages.

Finally, we discuss limits to the statistical analysis due to data sparseness. In particular, we show that the data available to Atkinson did not contain enough language families with sufficiently many languages to test whether the observed effect holds once random by-family slopes (for the effect) are included in the model. We also present simulations that show that the Type I error rate (false rejections) of the approach taken in Atkinson is many times higher than conventionally accepted (i.e. above .2 when .05 is the conventionally accepted rate of Type errors).

The scripts presented below are

*not*intended to allow full replication of our analyses (they lack annotation and we are not allowed to share the WALS data employed by Atkinson on this site anyway). However, there are many plots and tests in the paper that might be useful for typologists or other users of mixed models. For that reason, I am for now posting the raw code. Please comment below if you have questions and we will try to provide additional annotation for the scripts as needed and as time permits.**If you find (parts of the) script(s) useful, please consider citing our article in Linguistic Typology.**