USING COMMERCIAL LIST INFORMATION IN SCREENING ELIGIBLE HOUSING UNITS

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dc.contributor.advisorValliant, Richarden_US
dc.contributor.authorMaze, Alenaen_US
dc.contributor.departmentMathematical Statisticsen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2022-01-14T06:30:13Z
dc.date.available2022-01-14T06:30:13Z
dc.date.issued2021en_US
dc.description.abstractWhen using commercial address lists to sample households, investigators spend considerable time and money on screening households for eligibility as well as locating certain subpopulations (to achieve target sample sizes). Utilizing the demographic information on these lists to target eligible persons and subgroups has the potential to lower costs and field workers workload. Unfortunately, the information attached to the lists is error prone. We propose to evaluate the use of demographic information available on commercial lists in multistage household sampling. Specifically, this research will study how to efficiently design a three-stage sample that involves screening of housing units to determine eligibility. This research will also examine more complex estimators than have been previously studied. The goals of this study are to (1) estimate the accuracy rates in which commercial lists can correctly identify households with certain characteristics (e.g., Hispanics, Non-Hispanic Blacks, etc.); (2) Derive a theoretical variance formula, including variance components, for estimated totals; (3) Estimate variance components and evaluate alternative variance component estimators (design-based ANOVA, anticipated variance (model + design)); (4) Determine how to allocate two and three stage samples supplemented with commercial lists accounting for inaccuracy of listings, costs at each stage of sampling, target sample sizes and coefficient of variations (CVs), stratification of SSUs, and stratification of HU’s by MSG characteristics (e.g., Race/Ethnicity, ages of persons in HU, etc.). This research seeks to better understand the quality of demographic data attached to commercial lists and to use this information to increase sampling efficiency in the HRS by recovering more information for lower costs. This research potentially creates an improved sample design for HRS and similar surveys that is less costly and equally or more statistically efficient than the current design. In particular, the proposed design will help sample designers reduce the amount of housing unit screening needed to identify target subpopulations (e.g., Blacks, Hispanics, teenagers, and females). Furthermore, the results of this research will extend to other multistage household surveys that use commercial lists for sampling.en_US
dc.identifierhttps://doi.org/10.13016/xdzx-dto7
dc.identifier.urihttp://hdl.handle.net/1903/28296
dc.language.isoenen_US
dc.subject.pqcontrolledStatisticsen_US
dc.subject.pqcontrolledSocial researchen_US
dc.subject.pquncontrolledaddress based samplingen_US
dc.subject.pquncontrolledcommercial listsen_US
dc.subject.pquncontrolledcomplex variance estimatorsen_US
dc.subject.pquncontrolledsamplingen_US
dc.titleUSING COMMERCIAL LIST INFORMATION IN SCREENING ELIGIBLE HOUSING UNITSen_US
dc.typeDissertationen_US

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