Enumerating the Hidden Homeless: Strategies to Estimate the Homeless Gone Missing From a Point-in-Time Count
To receive federal homeless funds, communities are required to produce statistically reliable, unduplicated counts or estimates of homeless persons in sheltered and unsheltered locations during a one-night period (within the last ten days of January) called a point-in-time (PIT) count. In Los Angele...
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doaj-7530d4d9caef44e294f3d84bdc78cfc82021-09-06T19:41:46ZengSciendoJournal of Official Statistics2001-73672014-06-0130221522910.2478/jos-2014-0014jos-2014-0014Enumerating the Hidden Homeless: Strategies to Estimate the Homeless Gone Missing From a Point-in-Time CountAgans Robert P.0Jefferson Malcolm T.1Bowling James M.2Zeng Donglin3Yang Jenny4Silverbush Mark5University of North Carolina, Carolina Survey Research Laboratory, 730 Martin Luther King Jr. Blvd., Bolin Creek Center, Chapel Hill, NC, U.S.A.University of North Carolina, Carolina Survey Research Laboratory, 730 Martin Luther King Jr. Blvd., Bolin Creek Center, Chapel Hill, NC, U.S.A.University of North Carolina, Carolina Survey Research Laboratory, 730 Martin Luther King Jr. Blvd., Bolin Creek Center, Chapel Hill, NC, U.S.A.University of North Carolina, Carolina Survey Research Laboratory, 730 Martin Luther King Jr. Blvd., Bolin Creek Center, Chapel Hill, NC, U.S.A.University of North Carolina, Carolina Survey Research Laboratory, 730 Martin Luther King Jr. Blvd., Bolin Creek Center, Chapel Hill, NC, U.S.A.Los Angeles Homeless Services Authority, 811 Wilshare Blvd., Los Angeles, CA 90017, U.S.ATo receive federal homeless funds, communities are required to produce statistically reliable, unduplicated counts or estimates of homeless persons in sheltered and unsheltered locations during a one-night period (within the last ten days of January) called a point-in-time (PIT) count. In Los Angeles, a general population telephone survey was implemented to estimate the number of unsheltered homeless adults who are hidden from view during the PIT count. Two estimation approaches were investigated: i) the number of homeless persons identified as living on private property, which employed a conventional household weight for the estimated total (Horvitz-Thompson approach); and ii) the number of homeless persons identified as living on a neighbor’s property, which employed an additional adjustment derived from the size of the neighborhood network to estimate the total (multiplicity-based approach). This article compares the results of these two methods and discusses the implications therein.https://doi.org/10.2478/jos-2014-0014homeless counthidden homelessunsheltered homeless populationhorvitz-thompson estimatormultiplicity-based estimator |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Agans Robert P. Jefferson Malcolm T. Bowling James M. Zeng Donglin Yang Jenny Silverbush Mark |
spellingShingle |
Agans Robert P. Jefferson Malcolm T. Bowling James M. Zeng Donglin Yang Jenny Silverbush Mark Enumerating the Hidden Homeless: Strategies to Estimate the Homeless Gone Missing From a Point-in-Time Count Journal of Official Statistics homeless count hidden homeless unsheltered homeless population horvitz-thompson estimator multiplicity-based estimator |
author_facet |
Agans Robert P. Jefferson Malcolm T. Bowling James M. Zeng Donglin Yang Jenny Silverbush Mark |
author_sort |
Agans Robert P. |
title |
Enumerating the Hidden Homeless: Strategies to Estimate the Homeless Gone Missing From a Point-in-Time Count |
title_short |
Enumerating the Hidden Homeless: Strategies to Estimate the Homeless Gone Missing From a Point-in-Time Count |
title_full |
Enumerating the Hidden Homeless: Strategies to Estimate the Homeless Gone Missing From a Point-in-Time Count |
title_fullStr |
Enumerating the Hidden Homeless: Strategies to Estimate the Homeless Gone Missing From a Point-in-Time Count |
title_full_unstemmed |
Enumerating the Hidden Homeless: Strategies to Estimate the Homeless Gone Missing From a Point-in-Time Count |
title_sort |
enumerating the hidden homeless: strategies to estimate the homeless gone missing from a point-in-time count |
publisher |
Sciendo |
series |
Journal of Official Statistics |
issn |
2001-7367 |
publishDate |
2014-06-01 |
description |
To receive federal homeless funds, communities are required to produce statistically reliable, unduplicated counts or estimates of homeless persons in sheltered and unsheltered locations during a one-night period (within the last ten days of January) called a point-in-time (PIT) count. In Los Angeles, a general population telephone survey was implemented to estimate the number of unsheltered homeless adults who are hidden from view during the PIT count. Two estimation approaches were investigated: i) the number of homeless persons identified as living on private property, which employed a conventional household weight for the estimated total (Horvitz-Thompson approach); and ii) the number of homeless persons identified as living on a neighbor’s property, which employed an additional adjustment derived from the size of the neighborhood network to estimate the total (multiplicity-based approach). This article compares the results of these two methods and discusses the implications therein. |
topic |
homeless count hidden homeless unsheltered homeless population horvitz-thompson estimator multiplicity-based estimator |
url |
https://doi.org/10.2478/jos-2014-0014 |
work_keys_str_mv |
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