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Nadarajasundaram Ganesh

NORC at the University of Chicago



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Meena Khare

National Center for Health Statistics, CDC



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Elizabeth Ormson

NORC at the University of Chicago



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Wei Zeng

NORC at the University of Chicago



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Jenny Jeyarajah

National Center for Immunization and Respiratory Diseases



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David Yankey

National Center for Immunization and Respiratory Diseases



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Zhen Zhao

National Center for Immunization and Respiratory Diseases



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Kirk M. Wolter

NORC at the University of Chicago,



41 – Nonresponse Adjustment - 1

Noncoverage Adjustments in a Single-Frame Cell-Phone Survey: Weighting Approach to Adjust for Phoneless and Landline-Only Households

Sponsor: Survey Research Methods Section
Keywords: cell-phone sample, dual-frame sample design, noncoverage, RDD telephone surveys, single-frame sample design, weighting

Nadarajasundaram Ganesh

NORC at the University of Chicago

Meena Khare

National Center for Health Statistics, CDC

Elizabeth Ormson

NORC at the University of Chicago

Wei Zeng

NORC at the University of Chicago

Jenny Jeyarajah

National Center for Immunization and Respiratory Diseases

David Yankey

National Center for Immunization and Respiratory Diseases

Zhen Zhao

National Center for Immunization and Respiratory Diseases

Kirk M. Wolter

NORC at the University of Chicago,

In 2011, the National Immunization Survey (NIS) began using a dual-frame landline and cell-phone sample design to monitor vaccination coverage rates among children 19-35 months. As of 2012, coverage of the cell-phone sampling frame has increased to 92.9% of all age-eligible children in the NIS. Thus, a single-frame cell-phone sample design could be a viable option for the NIS, but such a sample design would not cover children living in landline-only and phoneless households. In order to adjust for the noncoverage of children living in landline-only and phoneless households, we propose two distinct adjustment methods. The first option is to identify a subset of cell-phone households with sampled children who have similar socio-demographic characteristics as those from landline-only and phoneless households and use a weighting class based approach to adjust for the noncoverage. The second option is to adjust for the noncoverage by using socio-demographic characteristics in a raking adjustment step. We implemented the proposed methods with 2012 NIS data and compared survey estimates generated under a single-frame cell-phone sample design with similar estimates from the current dual-frame sample design.

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