<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Item response rates frequently serve as indicators of data quality and potential nonresponse bias. However, key variables from surveys, such as total household income or net worth, are often composite variables constructed from several underlying components. Because such composite variables do not have clearly identifiable response rates, inference on the data quality of these key measures is more difficult. This article proposes three new methods for aggregating data on response rates across questions to create a measure of item response for composite variables. To compare the three methods and illustrate how they can be used (both individually and collectively) to investigate data quality, I analyze item response for net worth in the Survey of Income and Program Participation (SIPP) and the Survey of Consumer Finances (SCF). These new measures provide detailed information about net worth estimates that would be difficult to assess without an item response aggregation method. Overall, these new item response rate methods provide a new way of describing data quality for key measures in surveys and for analyzing changes in data quality over time.</p></abstract>

Item response rates frequently serve as indicators of data quality and potential nonresponse bias. However, key variables from surveys, such as total household income or net worth, are often composite variables constructed from several underlying components. Because such composite variables do not have clearly identifiable response rates, inference on the data quality of these key measures is more difficult. This article proposes three new methods for aggregating data on response rates across questions to create a measure of item response for composite variables. To compare the three methods and illustrate how they can be used (both individually and collectively) to investigate data quality, I analyze item response for net worth in the Survey of Income and Program Participation (SIPP) and the Survey of Consumer Finances (SCF). These new measures provide detailed information about net worth estimates that would be difficult to assess without an item response aggregation method. Overall, these new item response rate methods provide a new way of describing data quality for key measures in surveys and for analyzing changes in data quality over time.

Item Response Rates for Composite Variables

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Item Response Rates for Composite Variables"}

Item response rates frequently serve as indicators of data quality and potential nonresponse bias. However, key variables from surveys, such as total household...

Item Response Rates for Composite Variables

Publicado en línea: 18 jun 2019

Páginas: 387 - 408

Recibido: 01 abr 2018

Aceptado: 01 dic 2018

DOI: https://doi.org/10.2478/jos-2019-0018

Palabras clave
Response rates, nonresponse

© 2019 Jonathan Eggleston, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Item Response Rates for Composite Variables

Publicado en línea: 18 jun 2019

Páginas: 387 - 408

Recibido: 01 abr 2018

Aceptado: 01 dic 2018

DOI: https://doi.org/10.2478/jos-2019-0018

Palabras claveResponse rates, nonresponse

© 2019 Jonathan Eggleston, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Palabras clave
Response rates, nonresponse