189

and following the original publica-

tion of the book. Mrs. Natrella was an outstanding teacher and her pedagogical style comes through in her writings. After an introduction to basic statistical concepts, the book deals with virtually all of the statisti- cal decisions related to the analysis of data. More than 100 numerical examples are worked out in parallel to the statistical expressions applica- ble to the decision process under consideration. No other book of this kind will be more helpful to the data

analyst than this one by Natrella. The only shortcoming, if it is one, is that the examples are largely con-

Monitor w

cemed with ordinance problems. However, one should have no diffi- culty in relating them to other mea- surement problem areas. Several chapters on factorial experiments and statistical design are included to- gether with notes on statistical com- putations and the expression of un- certainties of final results. The con- cluding section contains 37 statistical tables that are essentially all that are used in the evaluation of experimen- tal data. If this reviewer were forced to dispose of most of the books in his library, Experimental Statistics would

be one of the last to go. One of the problems with govem-

Multiple Comparison Procedures, by Yosef Hochberg and Ajit C. Tamhane

Wiley, New York, 1987, XXII + 45Opp., price US $44.95, ISBN O-471 -82222-l

It is a rare occurrence when ex- actly one statistical test is calculated from experimental data. Investiga- tors naturally want to extract as much information as possible from their data, which often leads to multiple statistical tests. The problem which arises when a large number of tests are performed is that it becomes very likely some will indicate a significant result purely by chance. Methods for limiting the possibility of this kind of false result uniformly across a set of statistical tests are called multiple comparison methods.

A familiar example is the experi- ment involving several treatments, in which a number of comparisons

among the treatments are of interest. We might test each comparison at the 0.05 level, meaning that we limit the chance of a type I error (“finding something when there’s nothing”) to 0.05 for each test separately. How- ever, since the tests are related, the chance of a type I error for all the

tests together will be higher than 0.05, perhaps considerably higher, and will increase with the number of tests. To preserve the 0.05 level protection, clearly we must make each individual test at a more stringent level, and this is where multiple comparison meth- ods enter. Another aspect of the problem is whether the tests were specified when the experiment was planned, or chosen while exploring the data; in the first case, the number of tests is fixed, while in the second, potentially infinite. In addition, the aim of the experiment must be con- sidered: pilot studies or experiments to screen a large number of con- tenders have a different need for pro- tection from errors than confirma- tory experiments.

The fundamental principles for multiple comparisons were worked out between 1947 and 1955 by David Duncan, Henry Scheffe, and John Tukey. Many of us got our introduc- tion to the subject from the text by

ment publications is their limited

accessibility, especially to foreign purchasers. The publication of Ex- perimental Statistics by a commercial publisher should minimize this prob- lem and extend the availability of this indispensible reference work to an even wider audience.

JOHN K. TAYLOR Quality Assurance Consultant,

12816 Tern Drive, Gaithersburg IUD 20878, U.S.A.

D

Miller [l]. Miller’s colorful, trenchant writing and the book’s clear format have made it a classic. The book under review aims to provide a com- prehensive treatment of procedures for multiple comparisons, incorporat- ing recent advances and extensions to new areas. Hochberg and Tamhane limit their discussion to methods for comparing several treatments in the analysis of variance setting; several topics in Miller’s book, such as mul- tivariate methods and procedures for confidence bands and prediction in- tervals in linear regression, are not considered.

Hochberg and Tamhane aim to serve both statistical researchers and practitioners who want a cookbook, so their treatment is encyclopedic, with full mathematical derivations as well as numerical examples and ta- bles of distributions. All the standard parametric and non-parametric methods for comparing treatments are covered, generally at a more ab- stract level than Miller’s. A great deal of new material is presented, with detailed consideration of unbalanced designs, treatments with unequal variances, analysis of covariance, in- teraction contrasts, robust methods,

n Chemometrics and Intelligent Laboratory Systems 190

and special comparisons, such as comparisons with the best treatment and among ordered treatments. Other new material includes results on de- signing experiments for multiple comparisons (Chapter 6) and proce- dures based on Bayesian and deci- sion-theoretic approaches (Chapter 11).

As Hochberg and Tamhane re- mark (p. vii), although multiple com- parison procedures have been around for some time, “considerable confu- sion still exists in regard to what the

different [methods] provide, which ones should be used, and when.” Hochberg and Tamhane devote their first chapter to clarifying these issues through discussion and examples, with mixed results. Miller’s introduc- tory chapter provides a clearer, more accessible introduction to the subject.

Hochberg’s and Tan-mane’s book makes an important contribution to statistical practice, combining a thor- ough mathematical treatment with a wide survey of recent results. It should be helpful to investigators

analyzing experimental data with various complications, a situation which is the rule rather than the ex- ception.

Reference 1 R.G. Miller, Simultaneous Stutisti-

cal Inference, Springer Verlag, New York, 2nd ed., 1981.

WILLIAM THOMAS Texas A & M University,

College Station, TX, U.S.A.

-

m Meeting Reports

Databases for Analytical Chemists, Royal Society of Chemistry, BP Research Centre, Sunbury-on-Thames, U.K., 23 March 1988

This meeting was held jointly by the Information Group of the Royal Society of Chemistry (RSC) and the South Eastern Region of the RSC,

and involved both lectures and on- line presentations. The chairman was G.F. Phillips of the Laboratory of the Government Chemist.

H. Shalgosky (Harwell Labora- tory) discussed the information re- quirements of the analyst and the importance of consulting informa- tion sources such as reviews and ab- stracts to avoid repeating previously obtained data. It was possible to search about half a million references in 8 minutes using Boolean logic. There will still be problems with, for example, unpublished theses and commercial handbooks, and the large quantity of data not reported in the

formal published literature, so un- likely to be accessible via formal ab- stracting services. D. Spender (Orbit Search Service) reviewed the large number of available retrieval systems of which over 1000 are currently available. The Chemical Abstracts Database (8 million items since 1968) is a good example which is now available world-wide, both on-line and off-line. Other useful databases include Analytical Abstracts, Food

Science and Technology Abstracts, and a large number of specialist data- bases available to workers in various areas of chemistry. D. Walker (RSC, Nottingham, U.K.) continued the discussion of CAS Online, growing at 450,000 entries per year. Future trends will include CASREACT (list of organic reactions since 1985) and

SIN Express (which will enable building a search structure off-line using “templates” and predefining a

search strategy “hedge” before un- dertaking the search on-line). The Deputy Product Manager of RSC’s Analytical Abstracts, P. Read, de- scribed unique features of this on-line database including details of applica- bility, precision, experimental details and index features. The three on-line hosts are Orbit, Dialog and Data- Star. D. Head (BP, U.S.A.) described

archiving physical and chemical data and safety hints. Sophisticated world wide access to complex databases was discussed. S. Pantry (Health and Safety Executive) described chemical hazard information systems. The HSELINE database contains 100,000 current references and is growing at the rate of 12,500 per year. A com- pact disc system has been developed bringing together three major data- bases.

This meeting demonstrated the broad interest in chemical databas-