# Estimation in Surveys with Nonresponse

John Wiley & Sons, Aug 5, 2005 - Mathematics - 212 pages
Around the world a multitude of surveys are conducted every day, on a variety of subjects, and consequently surveys have become an accepted part of modern life. However, in recent years survey estimates have been increasingly affected by rising trends in nonresponse, with loss of accuracy as an undesirable result. Whilst it is possible to reduce nonresponse to some degree, it cannot be completely eliminated. Estimation techniques that account systematically for nonresponse and at the same time succeed in delivering acceptable accuracy are much needed.

Estimation in Surveys with Nonresponse provides an overview of these techniques, presenting the view of nonresponse as a normal (albeit undesirable) feature of a sample survey, one whose potentially harmful effects are to be minimised.

• Builds in the nonresponse feature of survey data collection as an integral part of the theory, both for point estimation and for variance estimation.
• Promotes weighting through calibration as a new and powerful technique for surveys with nonresponse.
• Highlights the analysis of nonresponse bias in estimates and methods to minimize this bias.
• Includes computational tools to help identify the best variables for calibration.
• Discusses the use of imputation as a complement to weighting by calibration.
• Contains guidelines for dealing with frame imperfections and coverage errors.
• Features worked examples throughout the text, using real data.

The accessible style of Estimation in Surveys with Nonresponse will make this an invaluable tool for survey methodologists in national statistics agencies and private survey agencies. Researchers, teachers, and students of statistics, social sciences and economics will benefit from the clear presentation and numerous examples.

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### Contents

 Chapter 1 Introduction 1 Chapter 2 The Survey and Its Imperfections 5 Chapter 3 General Principles to Assist Estimation 17 Chapter 4 The Use of Auxiliary Information under Ideal Conditions 29 Chapter 5 Introduction to Estimation in the Presence of Nonresponse 43 Chapter 6 Weighting of Data in the Presence of Nonresponse 49 Chapter 7 Examples of Calibration Estimators 67 Chapter 8 The Combined Use of Sample Information and Population Information 81
 Chapter 10 Selecting the Most Relevant Auxiliary Information 109 Chapter 11 Variance and Variance Estimation 135 Chapter 12 Imputation 153 Chapter 13 Variance Estimation in the Presence of Imputation 167 Chapter 14 Estimation Under Nonresponse and Frame Imperfections 179 References 191 Index 195 Copyright

 Chapter 9 Analysing the Bias due to Nonresponse 91