Last update: Jan., 2012.

For more information about my books and related data sets, or to download my R functions, go to

http://college.usc.edu/labs/rwilcox/home  Alink to my R functions is given below as well. Currently, there are over 950 R functions for applying a wide range of statisical techniques that are not readily available in standard statistical software. If you have any problems downloading the files from this web page, go to the other web page jusg indicated.

First, here is a list  and description of my current books:

Wilcox, R. R. (2003). Applying Contemporay Statistical Techniques. San Diego: Academic Press.

This book provides a two-semester, graduate level introduction to statistics. It covers standard techniques, explains modern insights regarding when and why they can be unsatisfactory, and it covers many modern robust and rank-based methods.

Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing, 3rd Edition. San Diego, CA: Academic Press.  Here is the table of contents: book2_toc

This book assumes the reader has had some training in statistics and focuses on modern robust and rank-based methods.

It contains most of the robust methods in my 2003 book plus a variety of other methods.

Wilcox, R. R. (2009). Basics Statistics: Understanding  Conventional Methods and Modern Insights. New York: Oxford University Press.
This book is intended for a one-semester  introduction to statistics. (I use it in our undergraduate statistics course.) The primary goal is to introduce standard topics typically covered, but in a manner that takes into account the major insights, typically ignored in an introductory course, which have taken place during the last half century. Included are explanations about when and why classic techniques fail and why serious practical problems with classic methods were missed for so many years. There are many examples broken down into small units in the hope of making the material relatively easy. A brief glimpse of modern techniques, aimed at dealing with known problems with classic methods, is provided. Errata are stored in errata_intro_stat

Wilcox, R. R. (2010). Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy, 2nd Ed. New York: Springer.

This book provides a very non-technical explanation of why classic methods are unsatisfactory under general conditions and the strategy behind more modern methods aimed at correcting known problems. It focuses on basics. For details about comparing multiple groups and more advanced topics on regression, my 2003 and 2005 books are preferable. For more information, go to  www.springer.com/978-1-4419-5524-1.

Wilcox (2012) Modern Statistics for the Social and Behavioral Sciences: A Practical Introduction. New York: CRC Press.

It covers standard methods typically covered in a basic graduate course plus a description of when and why classic methods fail as well as technically sound methods for dealing with known problems. Included are robust methods, developed during the last half century, for comparing groups and studying associatons. There are many practical advantages associated with modern methods, which are described and illustrated. R functions for applying classic methods, as well as more modern methods, are described. Here is the table of contents: book9_toc. Two corrections and a modification of one of the R functions are listed in errata_CRC_2012

My 2012 book published by CRC press, as well as the third edition of my book on robust methods, include a description of how to use my library of R functions. Starting  July, 2009, only the library  of R functions will be updated. An increasing number of functions run in R only, R is free, so the focus is on R.

A copy of my R functions is stored in Rallfun-v16.This file contains many new and improved R functions that are described in the third edition of my book

on robust methods as well as the 2012 book Modern Statistics for the Social and Behavioral Sciences, published by CRC press.

IF YOU HAVE A PROBLEM DOWNLOADING THE RALLFUN FILES, TRY THE WEB PAGE http://college.usc.edu/labs/rwilcox/home.

R PACKAGE

An R package can be downloaded from http://r-forge.r-project.org/projects/wrs/, thanks to efforts by Felix Schoenbrodt. Help files are being added; only a few are available now.

To install the package, first, be sure the most recent version of R is installed on your computer. Then use the R command

install.packages("WRS", repos="http://R-Forge.R-project.org")

If the most recent version of R is not installed, trying to install the WRS package should result in an error.

My most recent S-plus functions are stored in the file  allfun-v9. But no new functions will be added starting July, 2009.

(In case it is not obvious, you can save these files by clicking on them and using the save as command. Be sure to store them where   R (or S+) expects to find data, then use the source command to incorporate them into your version of R.) These files are recommended over earlier versions. It is recommended that you use version 2.2.0 of R or later. For information about new and modified functions, which are not described in any of my books, download the pdf file update_info.

I have updated the material that I use in workshops. There are four parts covering basics about modern methods, methods for comparing groups, methods for studying associations, and some descriptions and illustrations of my R and S+ functions. Some of the data sets are listed here. The first two deal with measures of depression among Palestinian youths who have or have not had a family member killed or wounded by an Israeli: depression1 depression2. These two data sets provide a particularly interesting example of how the shift function helps provide perspective on effect size. (Try the R function sband.).  The next data set, costa, deals with Olympic athletes who compete in sprints. The goal is to understand the association between two variables, one of which has to do with the force generated as the runner leaves the blocks. Many methods find no association, but certain methods suggest that an association exists. The file  schiz contains measures of skin resistance stemming from four groups of individuals having to do with schizophrenia.  The file read contains data on measures related to predicting reading ability in children. The files pygc and pyge  deal with what is called Pygmalion in the classroom and provide an interesting ANCOVA example. The data are described in my 2003 and 2005 books in the ANCOVA section.  The file  lake provides an interesting example of the effects of outliers when dealing with regression. Data on the sexual attitude of 1327 males and 2282 females are stored in miller. 

A workshop on robust methods was give during the summer of 2011:

Robust Statistics for Personality And Individual Differences

Bertinoro, Italy, July 16-21, 2011

Organizers: Jens B. Asendorpf & Marco Perugini

Supported by EAPP and ISSID. Here are the notes: summer_2011

Notes used in this workshop will be posted soon.

Notes from an old workshop are provided here in case they help.

The first part of the workshop,  work1 , discusses basic principles regarding why standard methods fail and how modern methods attempt to address known problems. Some introductory remarks about software are provided. Included is a discussion of detecting multivariate outliers and some of the issues that arise when outliers are discarded. The portion of the workshop that focuses on comparing groups is stored in work2. The file work3 contains information and illustrations regarding

regression. An introduction to R and S-plus and some illustrations on how to use my functions, beyond what is in my books, is covered in work4.