Estimating confidence limits on a standardised mortality ratio when the expected number is not error free.
The aim was to demonstrate how the beta distribution may be used to find confidence limits on a standardised mortality ratio (SMR) when the expected number of events is subject to random variation and to compare these limits with those obtained with the standard exact approach used for SMRs and with...
| Publicado en: | Journal of Epidemiology & Community Health Vol. 48; no. 3; pp. 313 - 318 |
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| Autor principal: | |
| Formato: | research Journal Article |
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BMJ Publishing Group
Jun1994
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104783926&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104783926 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0143005X C0H jtl: Journal of Epidemiology & Community Health issn: 0143005X maglogo: N pubinfo: dt: Jun1994 vid: 48 iid: 3 pid: 8280 pub: BMJ Publishing Group artinfo: ui: 104783926 104783926 2011143423 10.1136/jech.48.3.313 NLM8051534 PMC1059966 104783926 ppf: 313 ppct: 5 formats: tig: atl: Estimating confidence limits on a standardised mortality ratio when the expected number is not error free. aug: au: Silcocks, P affil: Department of Public Health Medicine, University of Sheffield Medical School. sug: subj: Confidence Intervals Epidemiological Research Mortality Adolescence Adult Aged Child Child, Preschool Prospective Studies Human Infant Leukemia, Myeloid Mortality Male Middle Age Software Statistics Methods Adolescent: 13-18 years Adult: 19-44 years Aged: 65+ years Child: 6-12 years Child, Preschool: 2-5 years Infant: 1-23 months Middle Aged: 45-64 years Male ab: The aim was to demonstrate how the beta distribution may be used to find confidence limits on a standardised mortality ratio (SMR) when the expected number of events is subject to random variation and to compare these limits with those obtained with the standard exact approach used for SMRs and with a Fieller-based confidence interval. The relationship of the binomial and the beta distributions is explained. For cohort studies in which deaths are counted in exposed and unexposed groups exact confidence limits on the relative risk are found conditional on the total number of observed deaths. A similar method for the SMR is justified by analogy between the SMR and the relative risk found from such cohort studies, and the fact that the relevant (beta) distribution does not require integer parameters. Illustrative examples of hypothetical data were used, together with a MINITAB macro (see appendix) to perform the calculations. Exact confidence intervals that include error in the expected number are much wider than those found with the standard exact method. Fieller intervals are comparable with the new exact method provided the observed and expected numbers (taken to be means of Poisson variates) are large enough to approximate normality. As the expected number is increased, the standard method gives results closer to the new method, but may still lead to different conclusions even with as many as 100 expected. If there is reason to suppose the expected number of deaths in an SMR is subject to sampling error (because of imprecisely estimated rates in the standard population) then exact confidence limits should be found by the methods described here, or approximate Fieller-based limits provided enough events are observed and expected to approximate normality. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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