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.}
}
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