Survey Nonresponse

A compendium of up–to–date research in survey nonresponse
Survey Nonresponse compiles theoretical and empirical research by noted experts to provide a current review of the field. It covers the behavioral underpinnings of non–response, its impact on the error structure of survey estimates, and current methods of adjusting the estimation process to account for nonresponse.
The volume combines literatures from social science and statistics to present a complete picture of modern methods of design and estimation in the face of missing survey data. The book is divided into four sections that discuss these fundamental issues: Alternative perspectives on causes and consequences of nonresponseCurrent theory and practice in survey protocols to reduce nonresponse ratesHow nonresponse varies systematically by various design featuresStatistical inference accounting for nonresponse
Survey Nonresponse can be used as a supplementary text for graduate students in survey methodology courses, or as a reference for researchers and professionals. It offers a balanced approach, up–to–date research, and thoroughly modern thinking on this vital subject.

Spis treści:
Contributors.
Preface.
PART I. PERSPECTIVES ON NONRESPONSE.
Survey Nonresponse in Design, Data Collection, and Analysis (D. Dillman, et al.).
Developing Nonresponse Standards (T. Smith).
Trends in Household Survey Nonresponse: A Longitudinal and International Comparison (E. de Leeuw and W. de Heer).
Culture and Survey Nonresponse (T. Johnson, et al.).
To Answer or Not to Answer: Decision Processes Related to Survey Item Nonresponse (P. Beatty and D. Herrmann).
The Causes of No–Opinion Response to Attitude Measures in Surveys: They Are Rarely What They Appear to Be (J. Krosnick).
PART II: IMPACTS OF SURVEY DESIGN ON NONRESPONSE.
The Influence of Interviewers′ Attitude and Behavio r on Household Survey Nonresponse: An International Comparison (J. Hox and E. de Leeuw).
Persuading Reluctant Recipients in Telephone Surveys (W. Dijkstra and J. Smit).
The Effects of Extended Interviewer Efforts on Nonresponse Bias (P. Lynn, et al.).
Effect of Item Nonresponse on Nonresponse Error and Inference (R. Mason, et al.).
The Use of Incentives to Reduce Nonresponse in Household Surveys (E. Singer).
The Influence of Alternative Visual Designs on Respondents′ Performance with Branching Instructions in Self–Administered Questionnaires (C. Redline and D. Dillman).
PART III: NONRESPONSE IN DIVERSE TYPES OF SURVEYS.
Evaluating Nonresponse Error in Mail Surveys (D. Moore and J. Tarnai).
Understanding Unit and Item Nonresponse in Business Surveys (D. Willimack, et al.).
Nonresponse in Web Surveys (V. Vehovar, et al.).
Nonresponse in Exit Polls: A Conprehensive Analysis (D. Merkle and M. Edelman).
Nonresponse in the Second Wave of Longitudinal Household Surveys (J. Lepkowski and M. Couper).
PART IV: STATISTICAL INFERENCE ACCOUNTING FOR NONRESPONSE.
Weighting Nonresponse Adjustments Based on Auxiliary Information (J. Bethlehem).
Poststratification and Weighting Adjustments (A. Gelman and J. Carlin).
Replication Methods for Variance Estimation in Complex Surveys with Imputed Data (J. Shao).
Variance Estimation from Survey Data under Single Imputation (H. Lee, et al.).
Large–Scale Imputation for Complex Surveys (D. Marker, et al.).
A Congenial Overview and Investigation of Multiple Imputation Inferences under Uncongeniality (X. Meng).
Multivariate Imputation of Coarsened Survey Data on Household Wealth (S. Heeringa, et al.).
Modeling Nonignorable Attrition and Measurement Error in Panel Surveys: An Application to Travel Demand Modeling (D. Brownstone, et al.).
Using Matched Substitutes to Adjust for Nonignorable Nonresponse through Multiple Imputations (D. Rubin and E. Zanutto).
Using Administrative Records to Impute for Nonresponse (E. Zanutto and A. Zaslavsky).
Imputation for Wave Nonresponse: Existing Methods and a Time Series Approach (D. Pfeffermann and G. Nathan).
Diagnostics for the Practical Effects of Nonresponse Adjustment Methods (J. Eltinge).
References.
Index.

Nota biograficzna:
ROBERT M. GROVES, PhD, is a professor and a senior research scientist at the University of Michigan. He is also Director of the Joint Program in Survey Methodology, a consortium of the University of Maryland, University of Michigan, and Westat.
DON A. DILLMAN, PhD, is Professor of Sociology and Rural Sociology at Washington State University, a senior scientist for the Gallup Organization, and previously a senior survey methodologist at the U. S. Census Bureau.
JOHN L. ELTINGE, PhD, is a senior mathematical statistician at the U. S. Bureau of Labor Statistics and an associate professor in the Department of Statistics at Texas A&M University.
RODERICK J. A. LITTLE, PhD, is Professor and Chair of Biostatistics in the School of Public Health at the University of Michigan and a senior research scientist at its Institute for Social Research.

Okładka tylna:
A compendium of up–to–date research in survey nonresponse
Survey Nonresponse compiles theoretical and empirical research by noted experts to provide a current review of the field. It covers the behavioral underpinnings of non–response, its impact on the error structure of survey estimates, and current methods of adjusting the estimation process to account for nonresponse.
The volume combines literatures from social science and statistics to present a complete picture of modern methods of design and estimation in the face of missing survey data. The book is divided into four sections that discuss these fundamental issues: Alternative perspectives on causes and consequences of nonresponseCurrent theory and pr actice in survey protocols to reduce nonresponse ratesHow nonresponse varies systematically by various design featuresStatistical inference accounting for nonresponse
Survey Nonresponse can be used as a supplementary text for graduate students in survey methodology courses, or as a reference for researchers and professionals. It offers a balanced approach, up–to–date research, and thoroughly modern thinking on this vital subject.