3144 BOOK REVIEWS

Applications: analysis of animal abundance; anal-ysis of cepheid data; analysis of educational data;atmospheric sciences; decision analysis; DNA pro-�ling; environmental epidemiology; FMRI; quantalbioassay; robust institutional comparisons; screeningfor breast cancer; sequential clinical trials; servicequality modelling; spatially correlated disease andexposure data; signal and image processing, the NileRiver; uncertainty analysis of complex computercodes.

Theory and methods: AR(1) time series;atmospheric sciences; Bayes and frequentistapproaches; changepoint analysis; dangers of mod-elling via continuous distributions; data and modelveri�cation; errors in variables; extreme values;�xed-lag smoothing; Gaussian Markov random�elds; graphical diagnostics; hypothesis testing; in-formation theory; latent structure; marked pointprocesses; MCMC (convergence diagnostics, exactsampling, general purpose algorithms, importancesampling, simulated sintering); mixtures of graphi-cal models; model choice (averaging, choice, crit-icism and search); non-parametrics; non-stationarymodels; optimal design; predictive inference;prior=posterior mapping; quantifying surprise; re-gression and classi�cation; robust Bayes; smoothing;

spatio-temporally correlated data; time series; time-varying covariance; unit root models; wavelets.

The book is almost perfect, apart from a pro-duction lapse: page 118 is followed by pages135–150, then pages 119–134 appear. An indexwould notably increase the book’s friendliness,though the chapter titles and keywords provide areasonably good guide.Bayesian Statistics 6 will become a well-worn

reference for Bayesians who want to know moreabout their �eld, for frequentists and agnostics whowant to know how the Bayesian approach operatesin theory and practice, for theoreticians and prac-titioners. It will serve as a marvellous adjunct textfor an advanced masters or doctoral-level course inBayesian statistics. All statisticians who are inter-ested in the theory and practice of their craft willbene�t from and enjoy reading and owning thisbook.

T. A. LOUISSenior Statistician

The RAND Corporation1200, South Hayes Street

Arlington, VA 22202U.S.A.

6. DICTIONARY FOR CLINICAL TRIALS. Simon Day.Wiley, Chichester, U.K., 19. No. of pages: 250.Price: $19.99. ISBN 0471 98611 9

The intended readership for Dictionary for ClinicalTrials includes trialists, ethics committee members,those who work in regulatory agencies, medical per-sonnel or anyone else who works with clinical tri-als. In the preface the author explains that choiceof entries was personal, based on his experiencesand those of his colleagues, as well as on reviewof protocols, regulatory guidelines and other perti-nent documents. The majority of terms chosen werestatistical, since these were judged the least wellunderstood, but various common epidemiological,ethical, data management and medical terms wereincluded as well, being important in discussions ofstudy design and publication. The style ‘is aimedat being pragmatic and readable rather than purist’.As such the author acknowledges that statisticiansmay challenge the correctness of the explanationsof various items.The dictionary is not likely to be of substantial

help to statisticians already involved in clinical

trials. For the occasional unfamiliar term, the expla-nations are often too brief to be useful to someonein the �eld. For instance, both ‘direct access’ and‘sequential access’ are de�ned as methods of ac-cessing data on a physical storage device, with noexplanation to distinguish the two. Also as noted,there are a fair number of items to argue about sta-tistically.There is potential for this to be useful to people

less involved in trials, but there are some concerns.Some obvious items are missing, such as accrualrate, adherence, disease-free survival, ow sheet,large simple trial, minimum e�ective dose, perfor-mance status, recursive partitioning, remission, se-lection design, statistical centre and supportive care,or hard to �nd, such as spending function (under al-pha spending function). Not all common usages areprovided. For instance, for cancer trials in the U.S.,phase I trials are dose �nding and phase II trialsestablish anti-tumour activity. The de�nitions in thedictionary, however, indicate that phase I trials arepharmacokinetic or toxicity studies while phase IItrials are dose �nding. Two-stage stopping rule canrefer to a design with one interim analysis as well

Copyright ? 2000 John Wiley & Sons, Ltd. Statist. Med. 2000; 19:3136–3145

BOOK REVIEWS 3145

as the dictionary’s de�nition of a rule requiring twocriteria to be met. ‘Advocate’ in the U.S. refers to apatient advocate, a champion of patient interests; thedictionary says only ‘to support a given argument,opinion or point of view’. Also, ethnicity and raceare not uniformly considered to be equivalent in theU.S. (it was particularly amusing to see ‘British’and ‘American’ listed as races in a sample table).For another example, ‘sphericity’ is de�ned as ‘theproperty that all the variances and covariances in aset of multivariate data are equal’; this is not thede�nition in my books.Some de�nitions are confusing (for example, rel-

ative frequency is de�ned as ‘the number of timesan event occurs divided by the total number ofevents that occurred’; in the con�dence interval itemsigni�cance tests are stated to ‘compare parameterswith arbitrary values’; ratio data is de�ned as ‘con-tinuous data that has a �xed zero’). Some cross-references are missing (for example, product limitestimate does not refer back to Kaplan–Meier esti-mate). Other de�nitions are unhelpful (the Heisen-berg uncertainty principle is not a factor in clinicaltrials). Some are misstated (Bayes theorem is nota process; serum is not formed when blood clots,it separates; multimodal is not a tautology). Unfor-tunately, the occasional item is simply wrong (forexample, the Wilcoxon rank sum test is not thesame test as the Wilcoxon matched pairs signedrank test).Perhaps of most concern is that the dictionary is

uneven in explanations of why certain things

are important or what major concerns might be. Theitem on outcomes research, for instance, is good(cheaper and faster than trials, but rigour and con-trol of bias are lost); on the other hand, there isno statement concerning potential problems (eitherethical or statistical) with a Zelen design. The itemon imputation is good (indicating assumptions maybe questionable); however, both the items on fac-torial design and overview note advantages but ne-glect to note disadvantages. Other items where anadditional line would have been helpful include themultiple comparisons items (it is not stated why ad-justments are needed); subgroup analyses (noted aspotentially misleading but not why); systematic al-location (potential for abuse and bias is not noted);and surrogate (it is not noted that theseare rarely adequate substitutes for the real end-point).Considering the limitations, this dictionary

would probably best be used as a supplement toa more comprehensive book explaining the princi-ples and pitfalls of clinical trials design, such asthe ones listed in the dictionary or one of the var-ious disease oriented clinical trials booksavailable.

STEPHANIE GREENFred Hutchinson Cancer Research Center

1100 Fairview Ave. N., MP557P.O. Box 19024

Seattle, WA 98109-1024, U.S.A.

Copyright ? 2000 John Wiley & Sons, Ltd. Statist. Med. 2000; 19:3136–3145