STATISTICS IN MEDICINEStatist. Med. 2004; 23:2151–2153

BOOKREVIEWSEditor: PetraMacaskill

1. Annette J. Dobson, An Introduction to Generalized Linear Models.

2. John Crowley (ed.), Statistics in Clinical Oncology.

1. AN INTRODUCTION TO GENERALIZED LINEARMODELS. 2nd edn. Annette J. Dobson, Chapman &Hall/CRC, London, 2002. No. of pages: IX+225.Price: $49.95. ISBN 1-58488-165-8

The second edition of this well-known text AnIntroduction to Generalized Linear Models byAnnette Dobson improves upon the already well-written and comprehensive overview of general-ized linear models presented in the �rst edition(1990). The updated text seeks to, and is suc-cessful in, �lling a void in the otherwise sparseliterature on the subject of generalized linear mod-els at the introductory level. The text is especiallydesigned for a reader unfamiliar with the subjectof linear and generalized linear models who hassome statistical background and understanding ofmatrix algebra, although my impression is that areader with only a minimal grasp of mathematicscould still bene�t to a lesser degree from readingthis text.The scope of the book, rearranged somewhat

from the �rst edition, covers topics includingexplanatory chapters on the exponential family,general model �tting, estimation and inference.Separate chapters are then devoted to di�erentgeneralized linear models, such as the normallinear model, logistic regression and Poisson re-gression, all very commonly seen generalizedlinear models. These chapters cover a fairly largenumber of topics very brie�y. The second editionhas expanded to incorporate chapters on rapidlydeveloping topics, including a very well-writtenchapter on survival analysis. A less clearly writtenchapter on cluster and longitudinal analysis is also

included, and could have been left out withoutcompromising the focus and relevance of the text.A current list of software that may be used to �tgeneralized linear models is provided which is veryhelpful.A skillful use of examples is a strength of this

text – a wide range of research applications arecovered and ample workings are also provided toaid the reader in statistical calculations. Manymoregraphs have also been included in the second edi-tion, enhancing the worded, explanations.In the quest to provide more explicit explana-

tions and a wider range of topics while keepingthe overall length of the text to a minimum, someof the simplicity and brevity of the �rst editionhas been lost, and on occasion, the written text ap-pears cramped. Also, while some mention is madeto other textbooks in many of the chapters, it mayhave been desirable to include more speci�c refer-ences within each section, given that the text cov-ers many topics very brie�y.Overall, I would highly recommend this text for

a reader interested in �nding out at an introductorylevel what the subject area of generalized linearmodels is all about, including the non-statistician,undergraduate and graduate-level student.

KERRIE NELSONDepartment of Statistics

LeConte CollegeUniversity of South Carolina

ColumbiaSouth Carolina 29208, U.S.A.

(DOI: 10.1002/sim.1493)

2. STATISTICS IN CLINICAL ONCOLOGY. John Crow-ley (ed.), Marcel Dekker, New York, 2001. Price:$175.00. ISBN: 0-8247-9025-1

This volume comprises contributions fromsome 43 biostatistical experts examining me-thodological issues arising in the design and

analysis of clinical trials as related to oncol-ogy. Traditionally, studies in oncology haveprovided a wealth of methodological ques-tions to challenge biostatisticians, especially inthe context of censored observations, multiplefailures and more recently, prognostic factormodelling.

Copyright ? 2004 John Wiley & Sons, Ltd.