R-Sessions 30: Visualizing missing values

It always takes some time to get a grip on a new dataset, especially large ones. The code-books are often as indispensable as they are massive, and not always as clear as one would want. Routings, and resulting and strange patterns of missing values are at times difficult to find.

I found a nice way to plot missing values, using R. Basically, I thought it would be nice to calculate the percentage of missings on each variable, and do so for each year represented in the data. These numbers could be visualized using a levelplot(), which resulted in the graph below.

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R-Sessions 29: Running R-Project twice on Apple Mac OS X

Working with statistics can be quite time consuming. As anyone working with relatively advanced models and large amounts of data knows, especially the waiting can be excruciating. Your statistical software is locked up while crunching those numbers, while you’d actually prefer to run some minor procedures, such as post-estimations, testing some loops, or simply displaying the output of a previously estimated model. With Apple’s Mac OS X you now can run R-Project twice, making the most of your dual core processor. … Continue Reading

A Very Small Step for Read.isi …

My R-Project package Read.isi is named in the R Newsletter. Yes, I know, this is just a very small step for my package Read.isi, especially because (almost?) every new package is named. Nevertheless, I’m proud of it.
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R-Sessions 28: Impressive R Speeds

Yesterday, I received my new Apple MacBook. It’s running a Core 2 Duo at 2.4 Ghz and it’s fast. Really fast!

Apparently, it’s very cool to show of the speed of R-Project on your system. Optimized .DLL files help to speed up your R on Windows systems (and possibly other systems as well) with respect to matrix transformations, which has led to enormous speed increases. So, let’s perform a speed-test of our own.
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The R-Sessions Forum: Introducing a new forum on R-Project

UPDATE: Due to lack of interest, and the availability of other excellent sources for interaction regarding R, I decided to close the R-Sessions forum, which now is no longer available. Questions on R can also be send to the author of this blog, by placing comments below.

Today, I introduce the new R-Sessions Forum: a new forum on R-Project and statistics in general. This new forum is closely integrated with Curving Normality, but has its own dynamic. The R-Sessions Forum aims at providing a flexible stage for visitors interested in discussing both R-Project and general statistics.

Topics & Features

The new R-Sessions Forum has several interesting features and covers many topics. Amongst the new topics covered are integration with the R-Sessions on Curving Normality, a section for general question on R, a section for general statistical questions, package specific questions, R development, and of course we have a pub for your general chatter. The integration with the R-Sessions is intended to give more dynamic ways of interacting with the Curving Normality web-site. The other topics are more general in nature and provide ample opportunity to pose your own questions and discuss those with other participants.

Do we really need this forum?

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R-Sessions 27: Text Editors for R: Textmate

R-Project works best with a good text editor that is well integrated with R-Project. This edition of the R-Sessions will focus on TextMate, a paid application marketed as ‘The Missing Editor for Mac OS X’.

Designed explicitly for use by programmers on Mac OS X, TextMate makes a promising first impression. The interface looks very clean, text is rendered perfectly, and syntax colouring is provided for quite a large number of programming languages. Also, the colouring of the syntax looks very nice, by the use of light colours that don’t interfere with reading the text.

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R Sessions 26: Text editors for R: Internal editor on OS X

Since R-Project is essentially syntax based, one needs a good text editor to write some code before it is executed in R. And, since we are all writing high quality code, we need a high quality text editor. This is the first in a series on text editors for using with R-Project on MacOSX.
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R-Sessions 25: Book – Mixed Effects Models in S and S-PLUS (Pinheiro & Bates, 2000)

Despite the reference to S and S-PLUS in the title of this book, it offers an excellent guide for the nlme-package in R-Project. Reason for this is the close resemblance between R and S. The nlme-package, available in R-Project for estimation of both linear and non-linear multilevel models, is written and maintained by the authors of this book.
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R-Sessions 24: Book: An R and S-PLUS Companion to Applied Regression (John Fox, 2002)

For those who have some theoretical knowledge on statistics and regression techniques, and who want to learn to use R-Project to analyze some data, John Fox wrote just the book.

The introductory chapter shows the most basic aspects of R-Project. Halfway this chapter the reader finds himself analyzing real data using regression techniques. The following chapters introduce the reader to other aspects of the analytical process: reading data into your statistical program, exploring the data and performing some bivariate tests. Then, three full chapters are devoted to regression techniques. While working on practical examples, the reader is introduced to more fundamental aspects of the R-Project software where needed.
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R-Sessions 23: Book: Data Analysis Using Regression and Multilevel/Hierarchical Models — Gelman & Hill (2007)

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman is known for his expertise on Bayesian statistics. Based on that knowledge he wrote a book in multilevel regression using R and WINbugs. This book aims to be a thorough description of (multilevel) regression techniques, implementation of these techniques in R and bugs, and a guide on interpreting the results of your analyses. Shortly put, the books excels on all three subjects.
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