Manova and above what's expected

Advanced Research Methods in Psychology will be welcomed by research students, taught postgraduates, and methodologically more confident undergraduates who need to have a systematic treatment of design approaches, data analysis and some of the wider aspects of research.

The preface gives a good idea of where the book is pitched: "...an accessible methods text that [will take] students on from the basics of Anova and regression, at the point where most psychology courses start to diverge on the basis of staff interests and expertise". It does indeed start beyond Anova, with chapters on Ancova, Manova and discriminant function analysis (but it goes a lot further).

There is a pretty good balance between explaining the underlying principles of these approaches sufficiently to satisfy the more numerically confident, and showing their practical use. The statistical technique is explained, a worked example is given, along with an illustrative study.

Part two looks at regression and other relationship techniques, including (new to me) logistic regression, and structural equation modelling. At this point in a book on "advanced" research methods, I must confess I was not expecting much else. But how wrong I was, and how surprising to find the author prepared to move on from the "high-profile" statistical techniques to the humbler domain of questionnaires and scale construction (so flexible and valuable to many students with more applied interests), the ever-helpful and flexible techniques of factor analysis, plus cluster analysis and other data-reduction techniques.

And there is more. We are now less than halfway through the book. Part four gives a significant introduction to a range of qualitative methods, again with illustrations from the literature of the techniques in use. Grounded theory and interpretative phenomenological analysis are there, but action research and feminist perspectives are also mentioned. I would commend the chapter 14 summary as a succinct picture of the place and relevance for particular kinds of qualitative approach within psychological research. Another chapter looks at particular issues around reporting and evaluating qualitative research.

Further chapters look at meta-analysis, repertory grid technique and aspects of research such as writing grant proposals and ethical issues. This is a book that should have been written years ago. It gives the fuller picture of research as it is done, in an accessible way. It will be relevant to students on a range of research-methods courses.

Research Methods and Statistics in Psychology is a widely used textbook, pitched at A-level psychology students and undergraduates. For its third edition, it gets a wash-and-brush-up with additional material on doing qualitative research and other updates. The text is well presented and includes glossaries, questions and answers, along with a marked practical report and synopses of qualitative reports, which will continue to be a staple for many courses.

Designing and Reporting Experiments in Psychology is focused, some might say narrowly, on the skills of writing reports of practical work, specifically that involving psychology experiments. It does this well. The recommendations are up to date and detailed, with chapters not only on methods, results and discussion but also on choosing the title of an experiment, writing an abstract and compiling references and appendices.

I would be quite happy to recommend students buy the book solely for part one, which covers how to write up your work. Part two is a detailed, well-presented treatment of the more traditional aspects of experimental design and statistics. It makes the book more complete, but other texts cover this well, so I would not necessarily recommend it for this. This edition claims to offer advice on more sophisticated report writing (with website support) and to be more up to date.

Making Sense of Data and Statistics in Psychology is not exciting. "Statistics" put me off - surely we should not be teaching statistics in psychology courses any more? Let the statisticians do this, while we share with students the ins and outs of collaborating with people to make sense of ourselves.

And yet many students do not get a good feel for statistics. This is a shame, for a good grasp of probability theory, how to graph data, the underlying principles behind statistical tests and so on provide a fine basis for data collection and the intelligent reading of research.

This is an old-fashioned sort of book students would find illuminating in understanding why they are being asked to collect data in a structured way and analyse numbers with statistical procedures. But excellent as the book is for this purpose, it is likely to be squeezed out of students' reading lists. At nearly £20 in paperback, it is not cheap, and its treatment is undoubtedly narrow. Check it out, though: it could be just what your course requires.

Research in Psychology: Methods and Design is a US-based text for students of experimental psychology. But with so many good UK texts around, colleagues may be prejudiced against this more expensive hardback volume. Yet it should not be dismissed; the US tradition is not to be ignored.

The book is comprehensive and has excellent appendices (writing lab reports, doing surveys, using statistics, statistical tables, answers to problems). There are 35 case studies illustrating different research issues. Arguably, it is authoritative in a way the UK texts are not ( Advanced Research Methods comes closest) in preaching a clear message about why psychology students should study psychological science. The book's second sentence reads: "I would like students to develop a clear sense of how experimental psychologists think." This is a thorough book that contains rich seams of information. Consider it seriously for the library and for student adoption on research-methods courses.

John Hegarty is lecturer in psychology, Keele University.