Indirect Sampling

  • Pierre Lavallée

Part of the Springer Series in Statistics book series (SSS)

Table of contents

  1. Front Matter
    Pages I-XVI
  2. Pierre Lavallée
    Pages 1-11
  3. Pierre Lavallée
    Pages 13-21
  4. Pierre Lavallée
    Pages 23-43
  5. Pierre Lavallée
    Pages 45-76
  6. Pierre Lavallée
    Pages 77-103
  7. Pierre Lavallée
    Pages 105-120
  8. Pierre Lavallée
    Pages 121-150
  9. Pierre Lavallée
    Pages 151-193
  10. Pierre Lavallée
    Pages 195-224
  11. Pierre Lavallée
    Pages 225-229
  12. Back Matter
    Pages 231-247

About this book

Introduction

Following the classical sampling theory, the survey statistician selects samples of people, businesses or others, in order to obtain the desired information. Drawing the samples is usually done by randomly selecting from a list representing the target population. In practice, this list is often not available. At best, the statistician only has access to a different list, indirectly related to the targeted population.

The example of a survey of children where the statistician only has a list of adult persons is a typical case. In this case, the statistician first draws a sample of adults, and for each selected adult, the statistician then identifies his/her children. The survey is done from the latter. This is what is called indirect sampling.

When indirect sampling is used jointly with the sampling of clusters of persons (families, for example), many complications arise for the survey statistician. One of the complications relates to the computation of the estimates from the survey. The production of estimates of simple totals or means can then become nightmares for the survey statistician. To solve this problem, the author proposes a simple solution, easy to implement, that is called the generalised weight share method.

This book is the reference on indirect sampling and the generalised weight share method. It contains the different developments done by the author on these subjects. The theory surrounding them is presented, but also different possible applications that drive its interest. The reader will find in this book the answer to questions that come, inevitably, when working in a context of indirect sampling.

Pierre Lavallée has been a survey statistician at Statistics Canada since 1985. He gas worked in social, business, and agricultural surveys. He has also worked for Eurostat in Luxembourg.

Keywords

clusters links production survey sampling unbiasedness weighting

Authors and affiliations

  • Pierre Lavallée
    • 1
  1. 1.Statistics CanadaOttawaCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-70782-2
  • Copyright Information Springer-Verlag New York 2007
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-387-70778-5
  • Online ISBN 978-0-387-70782-2
  • Series Print ISSN 0172-7397
  • About this book