Most scientific work is directed toward the search of causes and mechanisms and of ways to intervene on them to shape potential outcomes. Establishing causal explanation is never easy, but it is much simpler when the researcher has control over the experimental conditions, as often happens in basic science or in clinical trials. However, in many cases, it is not ethical or even possible to control or manipulate those conditions. How then can inferences be drawn? This volume, which contains revised and refined versions of the work presented at the 2008 Scientific Meeting of the American Psychopathological Association, attempts to provide some answers to this question.

The volume is divided into three parts. The first section, Causal Theory and Scientific Inference, encompasses transdisciplinary issues in causal inference. The second section, Innovation in Methods, presents new approaches for the development and testing of causal theories in epidemiology. The final section, Causal Thinking in Psychiatry, includes some critical analyses of causal claims in psychiatry by some of the leaders in the field.

This book, which is targeted mainly toward researchers, rather than toward clinicians, has the important virtue of offering something of interest to a broad variety of researchers. Investigators interested in causality but who do not have a strong mathematical background will benefit from reading Patrick Shrout's excellent introductory chapter, in which the main causal inferential methods are summarized at a very accessible level. Those interested in a brief introduction to genetics are likely to benefit from the complementary chapters by Kenneth Kendler on genetic epidemiology, George Davey Smith on Mendelian randomization, and Matthew State on rare variant approaches.

Some other chapters are more technical, such as those by Judea Pearl on nonparametric structural equation models and by Robbins and Richardson on three different counterfactual models that vary on the strength of their assumptions. The chapter by Muthén and colleagues on growth mixtures modeling is quite original in that it includes an introduction to these techniques at a level understandable to most mental health researchers, followed by an illustration of those methods with the example of a clinical trial. Murphy and colleagues present a succinct but comprehensive introduction to the logic and analyses of sequential multiple assignment randomized trials, including the formulae for analyzing those designs and the derivation of the formulae. These technical chapters are likely to attract the attention mainly of biostatisticians. However, they should also be read by clinical and epidemiological researchers who want to advance the field because they offer new conceptual and mathematical approaches to data analyses that are well-established in the statistical literature but are seldom used in psychiatry research.

The two final chapters, by Donald Klein, Robert Krueger, and Daniel Goldman, suggest some avenues to think about with regard to nosology and are particularly relevant in light of work on the upcoming DSM-5 as well as the recently unveiled Research Domain Criteria (1). Klein's chapter starts by discussing the concept of illness as applied to psychiatry and the problem of identifying a proper phenotype that can be later used to discover the factors that could cause that phenotype. Klein advocates the use of therapeutics as a means of identifying potential abnormalities that may be at the core of psychopathological processes, although he recognizes that his approach would require long-term, costly programmatic research. Krueger and Goldman nicely review dimensional approaches to psychopathology, explain how dimensional approaches provide an alternative (and often more powerful) conceptualization of psychopathology, and provide some examples of research questions that can be addressed using a dimensional approach. They end their chapter by advocating a dimensional approach to risk factors, a direction recently followed by Kenneth Kendler in an important study published in the Journal (2).

Perhaps an issue that receives relatively little attention is how to integrate different perspectives or approaches with causation. Phenomena and their causes can be examined at many levels, from the epidemiological to the molecular. At present, most researchers interested in causation in psychiatry focus on a particular level of causation. This may limit our theoretical perspectives on causation and the type of studies that we conduct. Maybe a multilevel approach to causation could help overcome some of the limitations of existing approaches.

In summary, this is an excellent book that can serve a broad range of readers. For some, it will serve as an introduction to the conceptual issues on causality. For others, it will provide new analytic approaches to complex data. For all, it can form the basis for a dialogue on how to improve the study of the causes and treatment of mental illness.