Book reviews

By now most population scientists are well acquainted with multilevel analysis, and many have applied multilevel models in the analysis of empirical data. Some researchers who have not thought of themselves as carrying out multilevel analysis recognize that they have applied equivalent models in the analysis of event-history data. Widely available statistical software, such as MlwiN (Rasbash et al. 2000), has eased the challenge of estimating rather complex multilevel models. To the accumulating stock of textbooks and journal articles (didactic and empirical studies), Daniel Courgeau has contributed this volume that is a blend of history, philosophy, and statistics. It is hardly surprising that Courgeau would assemble a volume with just this blend, since he has long occupied a singular position in the field, with his enthusiasm both for rather abstract excursions into the epistemology that governs the population sciences and for technical innovations that extend the frontiers of empirical research. Accordingly, the volume has a dual purpose: first, to consider how multilevel models can provide a more complete and balanced portrait of empirical reality than alternative models; and, second, to describe how multilevel analysis is performed, with particular attention to some recent technical innovations. This makes for an unusual and stimulating volume*/I am aware of no other collection of papers on multilevel analysis with this distinctive blend*/but also results in a work that is somewhat disjointed, with most chapters consisting either of theoretical discourse or presentation of technical material but not both. It seems that there are few scholars with Courgeau’s capacity to handle both kinds of material with intelligence and authority. In fact Courgeau’s own contributions constitute a substantial portion of this volume. There are eight chapters in total, and Courgeau is the sole author of three of them (including the Introduction and Conclusion) that together amount to roughly 90 of the 215 pages of text. In the Introduction and a chapter entitled ‘From the Macro /Micro Opposition to Multilevel Analysis in Demography’, Courgeau argues that multilevel models are the logical evolutionary progression beyond the simpler and inadequate models that demography employed in the past. To make this case, Courgeau submits a capsule review of the history of the field in which the dominant modes of analysis were, successively, the aggregate-period approach, cohort analysis, eventhistory analysis, and now multilevel analysis. His review provides an appropriate backdrop for the current hegemony of multilevel models, but it is questionable whether this history improves our understanding of multilevel analysis or will convert more researchers to their use. Indeed, the case for multilevel analysis in this volume*/in Courgeau’s Introduction and chapter ‘From the Macro /Micro Opposition . ’ and in a chapter by Ana V. Diez Rouz entitled ‘Potentialities and Limitations of Multilevel Analysis in Public Health and Epidemiology’*/for the most part will be entirely familiar to most readers. There is some value in having cogent contemporary statements of the case for multilevel models*/for inclusion in course syllabi, for example. But the reader will not find in these statements a rationale for such models that differs much from the rationale laid down in the 1980s and 1990s. In addition to Courgeau’s three contributions, the volume contains two other chapters that are largely theoretical in content. Bernard Walliser (‘Organizational Levels and Time Scales in Economics’) discusses the treatment of time and level of aggregation in economics. His discussion of time is, if anything, more elaborate and revealing than his discussion of level of aggregation. While time can be regarded as a level in multilevel analysis, the parallels with spatial and social levels are far from exact. Walliser’s discussion is compact and schematic, and I suspect that essays with this broad perspective on the epistemology of economics are rare. Robert Franck, who can be characterized as a philosopher of social science, devotes most of his chapter (‘Causal Analysis, System Analysis, and Multilevel Analysis: Philosophy and Epistemology’) to a discussion of the question of causality. His conclusion is that the constraints exercised by the social environment on behaviour*/constraints which he acknowledges are often very powerful*/are not Population Studies, Vol. 59, No. 1, 2005, pp. 119 /134