R. Harald Baayen, Anna Endresen, Laura A. Janda, Anastasia Makarova, Tore Nesset. Forthcoming. “Making Choices in Russian: Pros and Cons of Statistical Methods for Rival Forms” In a special issue of Russian Linguistics entitled Space and Time in Russian Temporal Expressions, guest edited by Stephen M. Dickey, Laura A. Janda, and Tore Nesset

This website provides data and R scripts for the analyses in our article.

NOTE: If you are already a proficient R user, skip down to the next horizontal line to get the data and R scripts.

How to download R

You can download the R statistical software package to your computer from the R project webpage. We recommend that you use the Austrian CRAN mirror since not all CRAN mirrors include the packages needed to run our scripts.

Once you have downloaded R, you will need to install the following packages: rms, Hmisc, party, modeltools, coin, mvtnorm, zoo, sandwich, strucchange, vcd, colorspace, ndl, lme4, languageR, multcomp. Use the Package Installer in the Menu and Get List to search for these packages.

How to download and run the files from this website

On this webpage we offer you two types of files that you can download to your computer. You can download these files by right-clicking on the links on this page. One of the files has the ".R" extension. This is an "R script". The R script contains all the commands that R needs in order to run the statistical test. You can open the R script if you like and see all the commands. We provide commentary on the commands in lines that begin with the "#" symbol (R itself ignores all these lines) in order to help you follow along. The other type of file has the ".csv" extension and contains a dataset. The R script performs the statistical analysis on this dataset. If you want to look at the dataset, you can open it with Microsoft Excel. It is important that you download both of these files to your home directory in your computer so that R can find them. If you do not know where your home directory is, you can also copy and paste the R commands from the scripts directly into the R window (see "Alternative methods for running R scripts" below). However, you will need to tell R where to find the .csv file with the dataset, by giving it the correct path, and you will have to put this into the R code.

How to run the files from this website in R

After you have downloaded an R script, you can open the R program on your computer. At the ">" prompt, type in: source("") and put the name of the R script you want to run between the quotation marks. For example, you can enter a line that looks like this: > source("LOAD.R") and when you hit the return key, R will run the R script and give you all of the results as output.

Alternative methods for running R scripts

If you simply click on the links with the R scripts, you can then copy and paste all of the code into the R window and R will run the commands and give you the same results. Another option is to download the R script to any location in your computer you want to and provide the path to the file when you use the source command. For example, you can enter a line that looks like this: > source("/Users/janedoe/Downloads/LOAD.R") for Mac users or > source("C://Documents/LOAD.R") for PC users. If you do not know the path, you can open your finder to where the R script is and then drag and drop that file into an open R window placing it after the cursor prompt ">". When you do this, R will tell you what the path to the file is and you can copy and paste that into the source command.

3.1 Грузить ‘load’ and its perfectives in the theme-object vs. goal-object constructions

This is the LOAD data: datLOAD.csv

This is the LOAD R script: LOAD.R

3.2 Пере- vs. пре-

This is the PERE data: datPERE.csv

This is the PERE R script: PERE.R

3.3 O- vs. Oб-

This is the OB data: datOB.csv

This is the OB R script: OB.R

3.4 -Ну vs. Ø

This is the NU data: datNU.csv

This is the NU R script: NU.R