Great Britain, 1995. No. of pages: xv + 359. Price: S32. ISBN: 0-412- 98431-9The central statistical model of this book is the non-linear mixed model for continuous responses, that is, a non-linear random regression model. The data structure can be thought of as one or more groups of individuals who are followed over a period of time over which some response is measured repeatedly.The book consists of 12 chapters, which can be roughly grouped into three categories: prerequisites; model formulation and inference, and applications.The prerequisite part comprises the first three chapters: the introduction; the fundamentals of ordinary non-linear regression, and the theory of hierarchical linear models (classical two-stage random regression models).The introductory chapter serves as a very fine appetizer, offering a series of examples with very clearly stated purposes.Chapter 2 gives an outline of the theory of ordinary non-linear regression (with only one 'individual'), with focus on the modelling of inhomogeneity in the variance as a parametric function of the mean. Useful practical and computational guidance is given, although in no detail.Chapter 3 gives an almost self-contained exposition of the classical normal theory inference in the hierarchical (two-stage) linear model (linear mixed effects model). The computation of ML and REML and best linear unbiased predictors (BLUP) for the random effects are given, and the relation to Bayes estimation is discussed. Numerical algorithms (Newton-Raphson, EM) are discussed, together with implementations in the standard software packages SAS, BMDP and S + . The last page gives an extremely useful bibliography.Chapters 2 and 3 together form the natural building bricks for the two-stage non-linear models, which are introduced in Chapter 4. The first stage of the model describes the mean value behaviour of a single individual as a non-linear function, depending on possible covariates, and with a specified variance and covariance structure which in theory can be quite arbitrary. In the second stage the parameters from the various individuals are assumed to follow some specified distribution, typically a normal distribution with unknown parameters.To be specific, the models considered allow for the following: A key issue in the use of such general models in applied work is the possibility of making adequate diagnostics. At present, few appropriate methods exist, and this book does not fill this gap. There are, however, some suggestions, for instance in the advice of the specification of the distribution of random effects. Whereas the normal distribution is usually assumed without much specific reason, it is here advocated to specify a more flexible class of distributions, allowing for bimodality, so that a possible inhomogeneity in the random effects can be detected and possibly included in the model as an explicit dependence on some covariate.A model this flexible can easily cause identifiability problems, as we approach the limit of information available in the data. Ofte...

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Sullrlmal~rInterferon 7 (IFN-3') is a pleiotropic cytokine secreted by T lymphocytes and natural killer (NK) cells and has been noted to be a first line of host defense in the control of viral infections. To examine further the role of this cytokine in the control of viral infections, mice with a targeted mutation in the IFN-7 gene were infected with influenza virus, and the in vivo antibody and ceil-mediated immune response to viral infection were examined. In addition, cell lines and clones were derived from the immunized animals and the in vitro cytokine production and cytotoxic T lymphocyte (CTL) response were analyzed. The absence of IFN-3' led to increased production of influenza-specific IgG1, IL-4, and IL-5 as compared to wild-type littermate control animals. In contrast, there was no difference noted in the development of an effective CTL response between IFN-7-deficient and wild-type animals. In this model of experimental influenza infection, IFN-7 is not necessary for the development of an effective humoral or cellular immune response to challenge with this respiratory virus.

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