Missing data and small-area estimation: modern analytical equipment for the survey statistician

Missing data and small-area estimation: modern analytical equipment for the survey statistician

Longford, Nicholas T.

80,03 €(IVA inc.)

This book develops methods for two key problems in the analysis of large-scale surveys: dealing with incomplete data and making inferences about sparsely represented subdomains. The presentation is committed to two particular methods, multiple imputation for missing data and multivariate composition for small-area estimation. The methods are presented as developments of established approaches by attending to their deficiencies. Thus the change to more efficient methods can be gradual, sensitive to the management priorities in large research organisations and multidisciplinary teams and to other reasons for inertia. The typical setting of each problem is addressed first, and then the constituency of the applications is widened to reinforce the view that the general method is essential for modern survey analysis. The general tone of the book is not "from theory to practice," but "from current practice to better practice." The third part of the book, a single chapter, presents a method for efficient estimation under model uncertainty. It is inspired by the solution for small-area estimation and is an example of "from good practice to better theory." .A strength of the presentation is chapters of case studies, one for each problem.Whenever possible, turning to examples and illustrations is preferred to the theoretical argument. The book is suitable for graduate students and researchers who are acquainted with the fundamentals of sampling theory and have a goodgrounding in statistical computing, or in conjunction with an intensive period of learning and establishing one's own a modern computing and graphical environment that would serve the reader for most of the analytical work in the future.While some analysts might regard data imperfections and deficiencies, suchas nonresponse and limited sample size, as someone else's failure that bars effective and valid.

  • ISBN: 978-1-84996-907-9
  • Editorial: Springer
  • Encuadernacion: Rústica
  • Fecha Publicación: 31/03/2012
  • Nº Volúmenes: 1
  • Idioma: Inglés