Creating spaghetti plots of eye-tracking data in R

I’ve been working on consolidating all the different R functions I’ve written over the years for plotting my eye-tracking data and creating just one amazing super-function (based on the ggplot2 package) that can do it all. Here’s a first attempt that anybody with the right kind of dataset should be able to use to create plots like the ones below (generated from fake data. The R code that generates the data is included at the end of the post). If you find this code helpful, please consider acknowledging it via the following URL in your paper/presentation to spread the word:

http://hlplab.wordpress.com/2012/02/27/creating-spaghetti-plots-of-eye-tracking-data-in-r/

Left: Empirical means with error bars indicating standard error for four experimental conditions. Contrast presence is coded in color, adjective type in line type. The first vertical line indicates adjective onset, the second ones indicate mean noun onset in each contrast condition. Right: Smoothed model estimates of proportions in each condition, with ribbons indicating 95% confidence intervals. Data from different subjects is plotted in different panels.

Google scholar now provides detailed citation report

This might be of interest to some of you: Google Scholar now allows you to correct links or citations to your work. It also provides a complete summary of all your citations, by article, by year, etc. It’s a functionality similar to academia.edu, but it let’s you remove wrong links to your work (e.g. to old prepublished manuscripts).

The interface is rather convenient since it allows you to import all references from scholar, which is almost 95% correct. Overall, it’s actually much more convenient than academia.edu (though I’d say it serves a slightly different purpose). It also generates a list of all your co-authors and other schnick-schnack . Check it out. Sweet.

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 demand – you can find the Computational Psycholinguistics class Roger Levy and I are currently teaching at the LSA 2011 institute at Boulder mirrored here.

Celebrating Tom Wasow: A Festschrift

At this year’s CUNY Sentence Processing Conference, Emily Bender and Jennifer Arnold presented a Festschrift celebrating Thomas Wasow. Here’s what the publisher’s site (CSLI) says (picture taken from the publisher’s website, which is hopefully ok; see the book for copyrights):

This book is a collection of papers on language processing, usage, and grammar, written in honor of Tom Wasow to commemorate his career on the occasion of his 65th birthday. Tom is a professor of linguistics and philosophy. But more accurately, he is a renaissance academic, having done work that connects with many different disciplines, including formal linguistics, sociolinguistics, historical linguistics, psycholinguistics, computational linguistics, and philosophy. Appropriately, this book reflects the diversity of Tom’s research and interests, including topics from multiple branches of linguistics and human information processing. These papers are written with minimal background assumed, so they can be used as teaching materials for beginning scholars. As such, this volume is a tribute to what is perhaps Tom’s most lasting contribution to the field—the mentorship and inspiration he provided to his students and collaborators, many of whom have contributed to this volume.

The book contains introductory and overview articles on a variety of topics in cognitive science from Emily M. Bender, Dan Flickinger, Stephan Oepen, Ash Asudeh, Peter Sells, Amy Perfors, James Paul Gee, John R. Rickford, T. Florian Jaeger, Jennifer E. Arnold, Harry J. Tily, Neal Snider, John A. Hawkins, and Susanne Riehemann.

LSA 2011 at Boulder: Yeah!

Woohooo. Roger Levy and I will be teaching a class on Computational Psycholinguistics at the 2011 LSA’s Linguistics Institute to be held July 5th- August 5th next year in Boulder, CO. The class description should be available through their website soon, but here are some snippets from our proposal:

CI fellow application for 2010 and onward due soon

If you’re thinking about joining HLP lab (or other computational labs) for 2010-2011/12 as a post-doc, consider applying to a CI fellowship. It’s highly competitive, but a super sweet deal. Here is what it says about eligibility and funding:

Eligibility. A CIFellow must have completed (or be prepared to complete) all requirements forgraduation from a U.S. Ph.D. program between May 1, 2009, and August 31, 2010. The Ph.D.must be in computer science, computer engineering, information science, or a closely relatedfield. Preference will be given to U.S. citizens and permanent residents, but others will be considered.

Award Size and Duration. We anticipate that awards will be for $75,000 salary for 12 monthswith approximately $25,000 for fringe benefits and a $15,000 allowance for moving, travel, anddiscretionary expenses. Host organizations will receive indirect costs at the 25% rate. The 12-month assignment must begin by November 1, 2010.

Good luck. (regardless of where you apply

Coming up: Mini-WoMM in Montreal

If you in the Montreal area, consider joining us for a Workshop on Ordinary and Multilevel Models to be held 5/3-4 at McGill and organized by Michael Wagner, Aparna Nadig, and Kris Onishi. The workshop will include the usual intros to linear regression, linear mixed models, logistic regression, and mixed logit models. We will also discuss common issues and solutions to regression modeling. Additionally, we will have a couple of special area lectures/tutorials:

• Maureen Gillespie (Northeastern) will talk about different ways to code your variables and how that relates to the specific hypotheses you’re testing.
• Peter Graff (MIT) will give a tutorial on logistic regression, specifically to test linguistic theories. In all likelihood, he will also sing. Which relates to the previous post, because he likes to sing about OT.

So, join us! I think there also will be a party =). Below is the full invitation (some details may change).

Some (very subjective) considerations for grad school

I’ve gotten some questions recently from foreign grad applicants about what they should pay attention to when choosing a graduate program (in psycholinguistics and/or linguistics and/or NLP).  So, here are some thoughts I have on this topic (note that Rochester doesn’t come on top in all of these categories). I am also hoping that some other people may chime in and maybe add to what I say or criticize me for it.

• Funding: the less worries about, the more you can focus on research. Also, the less teaching, the more you can focus on research.
• Freedom to conduct your own research vs. guidance: would you be admitted to work on a specific project or to develop your own research portfolio (under guidance of an advisor)? Maybe you prefer (to start) with a project that someone hands to you, maybe you really hate not being able whatever you want to do. Most often, the best solution will lie somewhere between these two extremes. For example, I prefer quite a lot of freedom rather than people looking over my should over the time, but there also needs to be guidance. I personally like to meet with students regularly once a week or every other week, depending on their preference. As an applicant, I would try to figure out whether you would get the mix of guidance and freedom that is right for you. This also extends beyond just research. Some programs will have many strict requirements (but hopefully there will also back that up with better structure in terms of their curriculum) compared to other places where there is a lot of ways to have your walk through your graduate career. Don’t be shy – ask
• Track record of the department/advisor: What jobs have graduates taken? If the department has a successful track record, does it hold up when you look at recent graduates (people who graduated 2-5 years ago)? Is the track record good in the subfield you want to go into? For example, some programs may be great NLP programs but would make it hard to get a job in a psychology department. Etc.
• Classes vs. research: obviously, you’ll need both, but what’s your preference and what does the place offer. Will you be asked to take classes until your 3rd or 4th year or do most students get their course work out of the way by the 2nd year? How flexible are the class requirements (how many “core” classes are you required to take? do they interest you?) Are the classes on topics you want to learn about? How early do students get involved in research? It may even be worth checking some grad student pages to see in what year of grad school they attended their first conference
• Avoid reliance on one advisor: I think this is an important consideration, but arguably not the most important.  I personally think it’s risky if there is only one person who you are really interested in at a place.  I think it’s best if there are at least two people you are excited about. Actually, we only admit students when at least two faculty members are really excited about them (though that is, of course, not the only criterion). Who knows maybe your interests will change a bit? Maybe that advisor will move away, maybe there are personal tensions, etc.
  • As a side point: It’s probably also a good idea to have a mix of junior and senior colleagues at the place.
• Gut instinct: At the end of the day, it comes down to the fact that you will spend a LOT of time with your advisors and colleagues — including your fellow students. So, I would trust my gut instinct. Did you get along with them? Do you feel you would have a good, productive, and exciting time in grad school? Will your colleagues motivate you to do great things or will you just feel bored or stressed (either one would make 5 years a loooooong time). That being said, I’d be cautious to not to just follow what you are familiar with. We usually feel more comfortable with what we familiar with, but it may not be the best move in the long run.

Tutorial on Regression and Mixed Models at Penn State

Last week (02/3-5/10), I had the pleasure to give the inaugural CLS Graduate Student Young Scientist Colloquium (“An information theoretic perspective on language production”) at the Center for Language Science at Penn State (State College).

I also gave two 3h-lectures on regression and mixed models. The slides for Day 1 introduce linear regression, generalized linear models, and generalized linear mixed models.  I am using example analyses of real psycholinguistic data sets from Harald Baayen’s languageR library (freely available through the free stats package R). The slides for Day 2 go through problems and solutions for regression models. For more information have a look at the online lectures available via the HLP lab wiki. I’ve uploaded the pdf slides and an R script. There also might be a pod cast available at some point. Feedback welcome. I’ll be giving a similar workshop at McGill in May, so watch for more materials.

I had an intensive and fun visit, meeting with researchers from Psychology, Communication and Disorders, Linguistics, Spanish, German, etc.  I learned a lot about bilingualism (not only though)  and a bit about anticipatory motor planning. So thanks to everyone there who helped to organize the visit, especially Jorge Valdes and Jee Sook Park. And thanks to Judith Kroll for the awesome cake (see below). Goes without saying that it was a pleasure meeting the unofficial mayor of State College, too . See you all at CUNY!

LSA09-125: Psycholinguistics and Syntactic Corpora

The LSA Summer Institute is almost over and it has been a lot of fun so far. I didn’t get to see nearly as many talks and classes as I had hoped to, but instead there were tons of interesting conversations, new ideas, and just nice moments hanging out in the sun.

Brief update: It couldn’t have been different — I missed my flight. That happens every time I try to leave the Bay area. I am so used to it, I am not even trying to be on time anymore . Ah well, it gives me a chance to enjoy a cappuccino in my favorite SF Cafe (Ritual Roasters) and even to attend Dan’s party (yippie!). Oh, and to upload some random pictures from the class room. Yeah, pretty dark I know. If you have better pictures — can you send them to me and I upload them? Also, here are some pics from our office hours at Caffee Strada (thanks to Judith and Alex for a great job!):

Random class room shot (2)

Random class room shot

Late night “office hours” at Jupiter’s

Michi smiling with TGrep2 at his command (almost!)

Judith and Alex working hard to spread the word of Switchboard

Judith (at hour 2 of 6)

hmm, probably at Jupiter’s again

LSA125-ers — thanks for an enjoyable class, for all the questions, and I hope you keep enjoying your projects (or, if nothing else, now know for certain that you really really never want to work with corpora . Send us an update about your papers as they progress.

To everyone else out there: If you’re interested in the use of syntactic corpora to investigate language production, you may find our LSA125 class webpage useful (see especially the links and information on the corpus pages, but also the slides). If you use material from this page, please let us know. Thanks to Judith, we now have a nicely documented version of the TGrep2 Database Tools, which we have dubbed TDTlite. Alex and Judith have also prepared example projects. TDTlite allows you to combine the output of TGrep2 searchers on syntactic corpora into a nice tab-delimited database that can be importated into R, Excel, or the stats program of your choice. While it doesn’t give you the full flexibility of scripting things yourself, it makes it considerably easier to start your own corpus-based project. We’re in the progress of polishing things up for distribution (thanks to all the brave members of our class who helped us to understand which parts still need further improvement!). So, if something like that might be of interest to you, let us know whether you would like further information. We hope to have a beta release by the end of August.

Multilevel model tutorial at Haskins lab

Austin Frank and I just gave a 2×3 hours workshop on multilevel models at Haskins Lab (thanks to Tine Mooshammer for organizing!). We had a great audience with a pretty diverse background (ranging from longitudinal studies on nutrition, over speech researchers, clinical studies, and psycholinguists, to fMRI researchers), which made for lots of interesting conversations on topics I don’t usually get to think about. Thanks to everyone attending =). We had a great time.

We may post the recordings once we receive them, if it turns out they may be useful. But for now, here are many of the slides we used, a substantial subset of which were created by Roger Levy (UC San Diego) and/or in collaboration with Victor Kuperman (Stanford University) for WOMM’09 at the CUNY Sentence Processing Conference, as indicated on the slides. No guarantees for the R-code and please do not distribute (rather: refer to this page) and ask before citing.

• Conceptual intro to Generalized Linear Models and Generalized Linear Mixed (a.k.a multilevel) models (based on WOMM’09 slides by Roger Levy with minimal changes by Florian Jaeger)
• Common issues in ordinary and multilevel regression modeling (based on Florian Jaeger & Victor Kuperman’s WOMM’09 slides plus some additional materials).
• Additional issues: multiple post-hoc comparisons and random effect ex/in-clusion (Austin Frank)

Questions and comments welcome, preferably using the comment box at the bottom of this page. R related questions should be send to the very friendly email support list for language researchers using R (see R-lang link in the navigation bar to the right).

Jaeger (2008), J Memory Language, 59, 434-446 (ANOVA)

Since I get asked for the R code I promised in my 2008 JML paper on mixed logit models every now and then, I have posted it here. If you find this code useful, please consider citing the Jaeger (2008) paper:

• Jaeger, T. Florian (2008). Categorical Data Analysis: Away from ANOVAs (transformation or not) and towards Logit Mixed Models. Journal of Memory and Language 59, 434-446. 

Please note, however, that the data analyzed in that paper is not mine and you need to acquire it from the Inbal Arnon (now at Manchester), who conducted the study. If you try to work your way through my paper, you may also find the following wiki pages from our lab with readings and more code helpful:

http://wiki.bcs.rochester.edu/HlpLab/StatsCourses/

As a quick intro you may find the talks from a recent workshop on the conceptual background, common issues and solutions for ordinary and multilevel regression models that some colleagues (Dale Barr, Roger Levy, Harald Baayen, Victor Kuperman, Austin Frank) and I gave at the CUNY sentence processing conference 2009 useful. The talk slides are all linked to the schedule on that page. You’ll find detailed walk-throughs, R code, and a conceptual overviews.

I appreciate if you leave a comment here in case this was useful. It helps to see what we should be posting. cheers.

 

Great new article about random speaker effects in sociolinguistic data analysis

Heya. I just wanted to bring the following nice article by Daniel Ezra Johnson to everyone’s attention:

Getting off the GoldVarb Standard: Introducing Rbrul for Mixed-Effects Variable Rule Analysis,
Daniel Ezra Johnson , University of York,
Language and Linguistics Compass 3/1
(2008): 359-383, doi: 10.1111/j.1749-818X.2008.00108.x
PDF:  http://www.blackwell-synergy.com/doi/pdf/10.1111/j.1749-818X.2008.00108.x

The article addresses the need for random speaker effect modeling in sociolinguistic data analysis and why researchers should switch from a Goldvarb standard to mixed effect models. The paper also describes an implementation available in R (Rbrul) that does affords both ordinary and multilevel regression modeling and is capable of formatting output in ways that either follow standard regression conventions or the Varbul standard which is more common in sociolinguistics and variationist work. I think the paper is really well written and provides some compelling arguments to use the more advance mixed effect models. Spread the word. There are still plenty of people out there who are hesitant to leave Goldvarb behind despite the obvious shortcoming that it does not support random effects.

Pre-CUNY Workshop on “Good practices in ordinary and multilevel regression models”?

Out of recent conversations with a whole bunch of folks (e.g. John Trueswell, Jennifer Arnold, Elsi Kaiser, Matt Traxler, Mike Tanenhaus, Jim Magnuson, and more), we came up with the idea to possible hold a workshop on “good practices in ordinary and multilevel regression models” [working title ] for researchers working on psycholinguistics/the psychology of language just a day before CUNY 2009 (to be held 03/26-28 at UC Davis), so 03/25 in Davis. This is just a baby of thought at this point, but if you’re interested, I’ve summarized some thoughts below and I’d appreciate your feedback (just leave a comment below and I will receive it).