Výsledky vyhledávání - "Stephen J. Kaputa"

An Embedded Experiment for Targeted Non-Response Follow-Up in Establishment Surveys

Autor: Stephen J. Kaputa, Katherine Jenny Thompson, Jennifer L. Beck

Publikováno v: Journal of the Royal Statistical Society Series A: Statistics in Society. 182:1371-1391

Summary The US Census Bureau is investigating adaptive non-response follow-up strategies for single-unit businesses in the 2017 Economic Census. The paper describes an embedded split-panel field experiment in the 2015 Annual Survey of Manufactures th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3986cd8d205e623fdc3a3104eb9dc4b5
https://doi.org/10.1111/rssa.12448

Zobrazit plný text záznamu

Plný text ve formátu HTML

Adaptive Design Strategies for Nonresponse Follow-Up in Economic Surveys

Autor: Katherine Jenny Thompson, Stephen J. Kaputa

Publikováno v: Journal of Official Statistics, Vol 34, Iss 2, Pp 445-462 (2018)

The U.S. Census Bureau is investigating nonrespondent subsampling strategies for use in the 2017 Economic Census. In previous research, we developed an optimized allocation procedure for subsampling nonrespondents that selects larger systematic sampl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca0e96a25eae9c584f3422091123619a
https://doi.org/10.2478/jos-2018-0020

Zobrazit plný text záznamu

Investigating Adaptive Nonresponse Follow-up Strategies for Small Businesses through Embedded Experiments

Autor: Katherine Jenny Thompson, Stephen J. Kaputa

Publikováno v: Journal of Official Statistics, Vol 33, Iss 3, Pp 835-856 (2017)

The U.S. Census Bureau is investigating adaptive Nonresponse Follow-Up (NRFU) strategies for single unit businesses in the 2017 Economic Census. These collection protocols require a suite of viable alternative procedures that can be implemented. With

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4799da48bb70165861abf9b8d6af1f5e
https://doi.org/10.1515/jos-2017-0038

Zobrazit plný text záznamu

Detecting and Treating Verified Influential Values in a Monthly Retail Trade Survey

Autor: Broderick Oliver, Stephen J. Kaputa, Mary H. Mulry

Publikováno v: Journal of Official Statistics, Vol 30, Iss 4, Pp 721-747 (2014)

In survey data, an observation is considered influential if it is reported correctly and its weighted contribution has an excessive effect on a key estimate, such as an estimate of total or change. In previous research with data from the U.S. Monthly

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ea9c2df4b0fff650714e0d6ed519ed0
https://doaj.org/article/b651e072f75d47a7b2a3510986fbec56

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání