2008•Unpublished venueRequires access

A Dual-Frame Design for the National Immunization Survey

Hee-Choon Shin, Noelle‐Angelique Molinari, Kirk Marcus Wolter

Open publisher page 3 citations

Abstract

The National Immunization Survey (NIS)—a nationwide, list-assisted random digit-dialing (RDD) survey conducted by the National Opinion Research Center (NORC) for the Centers for Disease Control and Prevention (CDC)—monitors the vaccination rates of children between the ages of 19 and 35 months. Each year, the NIS conducts interviews with approximately 24,000 households across the United States. We analyzed 2006 NIS data (children aged 19-35 months) and NIS-Teen data (children aged 13-17 years) data to determine the effect of directory-listed status on the immunization coverage rates. We considered alternative sampling designs by varying the proportion of directory-listed households, estimated population variances of the coverage rates for directorylisted and for unlisted households, and the unit cost of each completed interview from each frame. We confirmed that the proposed dual-frame design were more cost effective and not likely to introduce unacceptable new bias in the estimation. We have demonstrated the equivalence of UTD rates between children in listed and unlisted households, and the availability of efficiency gains by utilizing the proposed optimal stratified design. Therefore, other studies would benefit from this approach.

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What this paper is about

The National Immunization Survey (NIS)—a nationwide, list-assisted random digit-dialing (RDD) survey conducted by the National Opinion Research Center (NORC) for the Centers for Disease Control and Prevention (CDC)—monitors the vaccination rates of children between the ages of 19 and 35 months. Each year, the NIS conducts interviews with approximately 24,000 households across the United States. We analyzed 2006 NIS data (children aged 19-35 months) and NIS-Teen data (children aged 13-17 years) data to determine the effect of directory-listed status on the immunization coverage rates. We considered alternative sampling designs by varying the proportion of directory-listed households, estimated population variances of the coverage rates for directorylisted and for unlisted households, and the unit cost of each completed interview from each frame. We confirmed that the proposed dual-frame design were more cost effective and not likely to introduce unacceptable new bias in the estimation. We have demonstrated the equivalence of UTD rates between children in listed and unlisted households, and the availability of efficiency gains by utilizing the proposed optimal stratified design. Therefore, other studies would benefit from this approach.

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Available abstract

The National Immunization Survey (NIS)—a nationwide, list-assisted random digit-dialing (RDD) survey conducted by the National Opinion Research Center (NORC) for the Centers for Disease Control and Prevention (CDC)—monitors the vaccination rates of children between the ages of 19 and 35 months. Each year, the NIS conducts interviews with approximately 24,000 households across the United States. We analyzed 2006 NIS data (children aged 19-35 months) and NIS-Teen data (children aged 13-17 years) data to determine the effect of directory-listed status on the immunization coverage rates. We considered alternative sampling designs by varying the proportion of directory-listed households, estimated population variances of the coverage rates for directorylisted and for unlisted households, and the unit cost of each completed interview from each frame. We confirmed that the proposed dual-frame design were more cost effective and not likely to introduce unacceptable new bias in the estimation. We have demonstrated the equivalence of UTD rates between children in listed and unlisted households, and the availability of efficiency gains by utilizing the proposed optimal stratified design. Therefore, other studies would benefit from this approach.

Key concepts: Random digit dialing, Disease control, Sampling frame, Population, Directory, Medicine, Stratified sampling, Immunization

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