1630 BOOK REVIEWS

REFERENCES E. B., Laszlo, J. and Stanley, W. ‘A time-depend- ent statistical model which relates currentclini- cal status to prognosis: application to advanced prostatic cancer’, Journal of Chronic Diseases, 33.491-499 (1980).

1. Gail, M. Evaluating serial cancer marker stud- ies in patients at risk of recurrent disease’, Bio- metrics, 37, 67-78 (198 I ) .

2. Myers, L. E.. Paulson, D. F., Berry, W. R., Cox,

3. STATISTICS FOR HEALTH PROFESSIONALS. Susan Shott, W. B. Saunders, Philadelphia, 1990. No. of pages: xii + 418. Price: f21.50/%29.95. ISBN: 0-7216- 8254-5

According to the author this book is aimed at ‘diverse health professionals’. Three features dis- tinguish it from the more run of the mill biostatist- ics textbooks. First the assumptions underlying each test are clearly stated, and the limitations and pitfalls described. Secondly, the enormous quant- ity of real data sets in both the examples and the exercises, complete with references, should satisfy the most critical ‘campaign for real data’ sup- porter. Thirdly, there is a welcome emphasis on estimation and confidence intervals, and use of computer packages, particularly SPSS and SAS.

The book can be divided into two parts: an introductory section starting with a chapter on experimental design, and then chapters on the traditional descriptive statistics, probability, ran- dom variables, sampling, estimation and the hypo- thesis testing. The second, intermediate, section covers one-way analysis of variance, one factor repeated measures analysis of variance, analysis of frequency data, non-parametric statistics, correla- tion and regression and two-way analysis of vari- ance. There are appendices on sample sizes and power, summarizing results for publication, and a wryly amusing one on consulting a statistician.

The first section is excellent, and would be suit- able for courses to the more laboratory or patient based disciplines such AS doctors or dentists. There is a lack of epidemiology which would restrict its usefulness for public health professionals.

The second section does not give formulae, but rather illustrates the methods using output from SPSS and SAS. Problems such as multiple testing, which are not dealt with adequately by the pack- age, are then addressed in detail. I have more reservations about the second section, not because of the way it is presented, but rather with the choice of material, and the fact that each topic is treated in isolation. The method I use most fre- quently in my work is multiple regression, and the idea of a general linear model is one of the great unifying themes in statistics, linking analysis of variance with regression, and when generalized with the analysis of frequency data. Here there is no underlying theme, little linking between chap-

ters, and multiple regression only gets a brief mention in the regression chapter. It surfaces again in the chapter on two-way analysis of variance, but only as the method used by SPSS to obtain the ANOVA table. Thus the simple extension to ana- lysis of covariance, which is surely a commonly required technique, is missed. I was disappointed by the chapter on one-way analysis of variance of repeated measures, since there was no real feel as to what the analysis might achieve, no time plots of data, and no mention of the use of summary measures. The example given was a crossover trial, but no attempt made to look at crossover effects or period effects. This chapter appeared mainly de- voted to an explanation of how SPSS tackles repeated measures.

There are a number of idiosyncrasies in the book, including the dismissal of Fisher’s Exact test on the argument that ‘it only works if the row and column totals never change when the sample changes’, and since this almost never happens the test is not recommended. Despite extensive cover- age of the analysis of frequency data the chi- squared test for trend is not mentioned. For the formulae for the Pearson and Spearman correla- tion coefficient the reader is referred to other texts. The pitfalls of interpreting correlation are well illustrated however. The end-papers contain flow diagrams to help the reader decide which test to use, but I was rather disconcerted to discover in the procedures for two independent samples, that if I answered ‘yes’ to the query ‘comparison of pro- portions? I was given the two sample z-test, and if I answered ‘no’ but then answered ‘association’ over ‘comparison’ to be given the chi-squared test. Despite the emphasis on confidence intervals there is no description of intervals associated with non- parametric tests.

Thus, the first half of the book would be useful for teaching elementary courses, particularly as a source of real-life examples. The second half might be useful as a reference for researchers who wish to carry out a n analysis such as two way ANOVA using SPSS and want help in interpreting the output.

MIKE CAMPBELL Medical Statistics and Computing

University of Southampton Southampton General Hospital

Southampton SO9 4 X Y , U .K .