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02.Sampling

This module provides a framework to understand coverage error and then discusses the coverage properties of phone surveys using different types of sampling frames. It also covers the implementation of different sampling methods for phone surveys, with their advantages and disadvantages. The module ends with an overview of each of the basic steps needed in a survey weighting adjustment, with a focu... view more

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Module Overview and Coverage Error

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Coverage Error: Coverage bias

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Coverage Error: Coverage considerations for phone surveys

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Phone numbers from panel or previously collected surveys

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Random-Digit Dialing: What is Random Digit Dialing?

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Random-Digit Dialing: Mitofsky-Waksberg method

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Random-Digit Dialing: List-assisted designs

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Random-Digit Dialing: Dual frame designs

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Phone number directories or listings: Coverage considerations

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Phone number directories or listings: Sampling considerations and weighting implications

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Phone number directories or listings: Multiple frame approach

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Weighting: Overview of the basic steps in weighting

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Weighting: Design/Base weights

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Weighting: Adjustments for unknown eligibility

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Weighting: Multiplicity adjustment

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Weighting: Frame integration

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Weighting: Within-household selection adjustment

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Weighting: Nonresponse adjustment

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Weighting: Calibration

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Weighting: Trimming

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Summary

About the Presenters

Raphael Nishimura, Ph.D.

Raphael Nishimura is the Director of Sampling Operations in Survey Research Operations at the Survey Research Center (SRC) in the Institute of Social Research of the University of Michigan. He has been working with sampling and survey statistics for over ten years. He holds a PhD in survey methodology from the University of Michigan and a bachelor’s degree in statistics from the University of São Paulo. His main research interest includes sampling methods, survey nonresponse and adaptive/responsive designs. He is also the director of the Sampling Program for Survey Statisticians of the SRC Summer Institute for Survey Research Techniques.