[Rd] Additional Books on R for Web Site Listing

[Marc Schwartz]

Hi all,

I noted that the books below are not included on the R web site
Documentation section under "Books". I thought that I would provide
these and have created some bib entries consistent with the style used
on the site. The abstract sections were copied from the publisher sites.

I hope that these are acceptable to both the book list maintainer and
the respective authors. Feel free to modify as may be appropriate.

It is great to see the increasing number of new books on R!

A special note to Paul Murrell on a great addition to the R library! I
just got my copy this past week from Amazon.com. Well Done!

Best regards,

Marc Schwartz



@BOOK{R:Crawley:2005,
  AUTHOR = {Michael J. Crawley},
  TITLE = {Statistics: An Introduction using R},
  PUBLISHER = {Wiley},
  YEAR = 2005,
  NOTE = {ISBN 0-470-02297-3},
  PUBLISHERURL = {http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470022973.html},
  URL = {http://www.bio.ic.ac.uk/research/crawley/statistics/},
  ABSTRACT = {Statistics: An Introduction using R is the first text to offer such
              a concise introduction to a broad array of statistical methods,
              at a level that is elementary enough to appeal to a broad range of
              disciplines. It is primarily aimed at undergraduate students in medicine,
              engineering, economics and biology – but will also appeal to postgraduates
              who have not previously covered this area, or wish to switch to using R.}
}



@BOOK{R:Everitt:2005,
  AUTHOR = {Brian S. Everitt},
  TITLE = {An R and S-Plus® Companion to Multivariate Analysis},
  PUBLISHER = {Springer},
  YEAR = 2005,
  NOTE = {ISBN 1-85233-882-2},
  PUBLISHERURL = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-40109-22-34953445-0,00.html},
  URL = {http://biostatistics.iop.kcl.ac.uk/publications/everitt/},
  ABSTRACT = {In this book the core multivariate methodology is covered along with some
              basic theory for each method described. The necessary R and S-PLUS code
              is given for each analysis in the book, with any differences between the
              two highlighted. A website with all the datasets and code used in the book
              can be found at http://biostatistics.iop.kcl.ac.uk/publications/everitt/.}
}



@BOOK{R:Harrell:2001,
  AUTHOR = {Frank E. Harrell},
  TITLE = {Regression Modeling Strategies, with Applications to Linear
  Models, Survival Analysis and Logistic Regression},
  PUBLISHER = {Springer},
  YEAR = 2001,
  NOTE = {ISBN 0-387-95232-2},
  PUBLISHERURL = {http://www.springeronline.com/sgw/cda/frontpage/0,11855,4-0-22-2187282-0,00.html},
  URL = {http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/RmS},
  ABSTRACT = {There are many books that are excellent sources of knowledge about individual statistical
              tools (survival models, general linear models, etc.), but the art of data analysis is
              about choosing and using multiple tools. In the words of Chatfield "...students typically
              know the technical details of regression for example, but not necessarily when and how to
              apply it. This argues the need for a better balance in the literature and in statistical
              teaching between techniques and problem solving strategies." Whether analyzing risk
              factors, adjusting for biases in observational studies, or developing predictive models,
              there are common problems that few regression texts address. For example, there are
              missing data in the majority of datasets one is likely to encounter (other than those
              used in textbooks!) but most regression texts do not include methods for dealing with
              such data effectively, and texts on missing data do not cover regression modeling.}
}