Analysis of Survey Data
vides an excellent precursor to the final chapter on Neural Networks (NN) which the authors highlight as being especially useful for dealing with longer data gaps that can be accurately dealt with using imputation. This fifth and final chapter is one of the real strengths of this text as a resource because it describes the origin of NN and how they are applicable. The remainder of the chapter uses illustrations and examples to aid in the readers’ understanding of NN and how they can be used to fill substantial data gaps. In reading this book and consulting with others, I was pleased to note that the majority of the book, but especially this chapter, was easily assessable to those without a graduate degree in statistics (provided they have some familiarity with the subject matter). This text is not meant to be a primary resource for classroom instruction because it deals with a very specific, albeit important, issue. Although the text does include detailed and well-illustrated examples, it does not provide exercises that are appropriate for a classroom setting. Instead, it functions well as a research reference for those dealing with ecological time series data that is inevitably plagued by both data errors (which results in excluding data from analyses) and missing observations. The book fills the reference niche well by providing straightforward answers to many of the questions subject matter researchers will ask, and perhaps more importantly, it does so in a relatively straightforward manner. The book includes a CD of what the authors refer to as “in-progress” software that accompanies the text. The first set of downloadable tools run on a Java platform while the second set consists of MATLAB code requiring that the user have this software available. The authors clearly specify that these tools are meant for research and assume the user has some familiarity with the program and platforms they are using as well as the subject matter. The website for the text also mentions a third tool that the authors hope to make available for download, which will help users manage their own time series data and fill data gaps using the appropriate techniques discussed in the book. This tool may prove to be an excellent companion to the book when it becomes available. Although the CD may be helpful for those who have the software to make use of it, it does not include the datasets discussed in the book in a format that could be imported into other software. Even without the software CD, however, this book is a valuable resource that should be useful to a wide variety of researchers.