Adaptive Survey Design

Regular price €56.99
A01=Andy Peytchev
A01=Barry Schouten
A01=James Wagner
Adaptive Designs
adaptive sampling
Adaptive Survey Design
Age Group_Uncategorized
Age Group_Uncategorized
Allocation Probabilities
Andy Peytchev
Author_Andy Peytchev
Author_Barry Schouten
Author_James Wagner
automatic-update
Auxiliary Variables
Call Attempts
Category1=Non-Fiction
Category=PBT
Contact Attempt
COP=United Kingdom
Data Sets
Delivery_Pre-order
eq_isMigrated=2
Estimated Response Propensities
James Wagner
Key Survey Variable
Language_English
measurement error
Modified Response Rate
Multi-purpose Surveys
nonresponse
Nonresponse Adjustment
Nonresponse Bias
PA=Temporarily unavailable
Postsurvey Adjustments
Price_€50 to €100
PS=Active
Reduce Nonresponse Bias
Response Propensities
Response Propensity Model
responsive design
Sample Management System
Sample Members
Sample Telephone Numbers
sensitivity analysis
Simulation Based Optimization Methods
softlaunch
stratification
Survey Design Features
Survey Design Parameters
Survey Outcome Variable
Survey Variables

Product details

  • ISBN 9780367735982
  • Weight: 500g
  • Dimensions: 156 x 234mm
  • Publication Date: 18 Dec 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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Adaptive survey designs (ASDs) provide a framework for data-driven tailoring of data collection procedures to different sample members, often for cost and bias reduction. People vary in how likely they are to respond and in how they respond. This variation leads to opportunities to selectively deploy design features in order to control both nonresponse and measurement errors. ASD aims at the optimal matching of design features and the characteristics of respondents given the survey budget. Such a goal is sensible, but ASD requires investment in more advanced technical systems and management infrastructure and asks for the collection of relevant auxiliary data. So what are current best practices in ASD? And is ASD worthwhile when the same auxiliary data are employed in the estimation afterwards? In this book, the authors provide answers to these questions, and much more.

Andy Peytchev is a research assistant professor in the University of Michigan’s Program in Survey Methodology and the Joint Program in Survey Methodology at the University of Maryland.

Barry Schouten is senior methodologist at Statistics Netherlands and professor at Utrecht University.

James Wagner is research associate professor in the University of Michigan’s Program in Survey Methodology and the Joint Program in Survey Methodology at the University of Maryland.