Statistical Methods for the Analysis of Time-Location Sampling Data.
Time-location sampling (TLS) is useful for collecting information on a hard-to-reach population (such as men who have sex with men [MSM]) by sampling locations where persons of interest can be found, and then sampling those who attend. These studies have typically been analyzed as a simple random sa...
| Publicado en: | Journal of Urban Health Vol. 89; no. 3; pp. 565 - 587 |
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| Autores principales: | , |
| Formato: | Artículo |
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Springer Nature
Jun2012
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=76350518&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 76350518 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10993460 GMF jtl: Journal of Urban Health issn: 10993460 maglogo: N pubinfo: dt: Jun2012 vid: 89 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 76350518 10.1007/s11524-012-9676-8 ppf: 565 ppct: 22 formats: fmt: @attributes: type: P size: 237KB tig: atl: Statistical Methods for the Analysis of Time-Location Sampling Data. aug: au: Karon, John Wejnert, Cyprian affil: Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta USA su: Men who have sex with men Statistical sampling Statistical weighting Sample size (Statistics) Health surveys sug: subj: Men who have sex with men Marketing Research and Public Opinion Polling Statistical sampling Statistical weighting Sample size (Statistics) Health surveys keyword: HIV Statistical methods Time-location sampling HIV Statistical methods Time-location sampling ab: Time-location sampling (TLS) is useful for collecting information on a hard-to-reach population (such as men who have sex with men [MSM]) by sampling locations where persons of interest can be found, and then sampling those who attend. These studies have typically been analyzed as a simple random sample (SRS) from the population of interest. If this population is the source population, as we assume here, such an analysis is likely to be biased, because it ignores possible associations between outcomes of interest and frequency of attendance at the locations sampled, and is likely to underestimate the uncertainty in the estimates, as a result of ignoring both the clustering within locations and the variation in the probability of sampling among members of the population who attend sampling locations. We propose that TLS data be analyzed as a two-stage sample survey using a simple weighting procedure based on the inverse of the approximate probability that a person was sampled and using sample survey analysis software to estimate the standard errors of estimates (to account for the effects of clustering within the first stage [locations] and variation in the weights). We use data from the Young Men's Survey Phase II, a study of MSM, to show that, compared with an analysis assuming a SRS, weighting can affect point prevalence estimates and estimates of associations and that weighting and clustering can substantially increase estimates of standard errors. We describe data on location attendance that would yield improved estimates of weights. We comment on the advantages and disadvantages of TLS and respondent-driven sampling. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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