FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1007382022> ?p ?o ?g. }

• W1007382022 endingPage "84" @default.
• W1007382022 startingPage "665" @default.
• W1007382022 abstract "This article reviews the current small-area variation analysis (SAVA) approach to population-based rates of surgery, and describes a new method for ascertaining variance based on the beta-binomial probability distribution of small-area rates. The critical review of the current SAVA approach focuses (1) on how incidence rates are calculated, and (2) on how the significance of the observed magnitude between the largest and smallest rates (i.e., the external quotient) is ascertained. While reducing the problems of calculating rates by considering only certain operative procedures, the new method addresses the current inadequacies of ascertaining significant differences among small areas. Not only does it correctly assess likelihood of an extermal quotient, it also can determine the particular area's rate, producing an unlikely extermal quotient. The method evaluates the probability that the observed magnitude of the extremal quotient is due solely to chance and study design effects, and tables of these probabilities are available for the method's application. A mathematical model, based on a combination of the binomial and beta distributions, uses (1) the sample size, (2) the average of the areas' rates, (3) the variance among the rates, and (4) a specific quotient level to determine the probability of observing the quotient by chance. After computerizing this calculation, probability tables for reasonable values of these four parameters are generated. In addition to looking at just one quotient for each sample, the probability tables facilitate the easy examination of intermediate quotients when the extremal quotient is unlikely due to chance. By alternatively ignoring the highest and lowest rates, two new quotients can be produced and tested. Given that one of these two quotients is likely due to chance, the excluded rate (i.e., producing the unlikely extremal quotient) can be classified as an outliner, and the associated small area should be the focus of more detailed investigation. The probability tables reveal that the external quotient is not the appropriate statistic to be applied in studies where many small areas are to be included. The probability of seeing even a large extremal quotient simply by chance rapidly approaches one as the sample size increases. However, an extremal quotient modeled from a beta-binomial distribution can be useful for studies with small sample sizes (e.g., six counties). The use of this beta-binomial model for small-area rates provides a new method of designing and evaluating small-area studies where costs or domain limit the number of areas under consideration.(ABSTRACT TRUNCATED AT 400 WORDS)" @default.
• W1007382022 created "2016-06-24" @default.
• W1007382022 creator A5019122430 @default.
• W1007382022 creator A5050976881 @default.
• W1007382022 creator A5064891410 @default.
• W1007382022 date "1989-12-01" @default.
• W1007382022 modified "2023-09-25" @default.
• W1007382022 title "The extremal quotient in small-area variation analysis." @default.
• W1007382022 cites W117937207 @default.
• W1007382022 cites W1424478545 @default.
• W1007382022 cites W1523424232 @default.
• W1007382022 cites W1966940033 @default.
• W1007382022 cites W1977870154 @default.
• W1007382022 cites W1978271134 @default.
• W1007382022 cites W1982496005 @default.
• W1007382022 cites W1992336204 @default.
• W1007382022 cites W1995409470 @default.
• W1007382022 cites W1999610599 @default.
• W1007382022 cites W2001542623 @default.
• W1007382022 cites W2013442713 @default.
• W1007382022 cites W2016870307 @default.
• W1007382022 cites W2030799926 @default.
• W1007382022 cites W2050857666 @default.
• W1007382022 cites W2055595527 @default.
• W1007382022 cites W2056441853 @default.
• W1007382022 cites W2062093372 @default.
• W1007382022 cites W2073048207 @default.
• W1007382022 cites W2083967436 @default.
• W1007382022 cites W2089327038 @default.
• W1007382022 cites W2092751356 @default.
• W1007382022 cites W2123366978 @default.
• W1007382022 cites W2326662050 @default.
• W1007382022 cites W2396604646 @default.
• W1007382022 cites W2401281286 @default.
• W1007382022 cites W2414769233 @default.
• W1007382022 cites W2419095327 @default.
• W1007382022 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/1065591" @default.
• W1007382022 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/2584039" @default.
• W1007382022 hasPublicationYear "1989" @default.
• W1007382022 type Work @default.
• W1007382022 sameAs 1007382022 @default.
• W1007382022 citedByCount "16" @default.
• W1007382022 countsByYear W10073820222013 @default.
• W1007382022 countsByYear W10073820222016 @default.
• W1007382022 countsByYear W10073820222019 @default.
• W1007382022 countsByYear W10073820222021 @default.
• W1007382022 crossrefType "journal-article" @default.
• W1007382022 hasAuthorship W1007382022A5019122430 @default.
• W1007382022 hasAuthorship W1007382022A5050976881 @default.
• W1007382022 hasAuthorship W1007382022A5064891410 @default.
• W1007382022 hasConcept C105795698 @default.
• W1007382022 hasConcept C114614502 @default.
• W1007382022 hasConcept C119599485 @default.
• W1007382022 hasConcept C121955636 @default.
• W1007382022 hasConcept C127413603 @default.
• W1007382022 hasConcept C129848803 @default.
• W1007382022 hasConcept C144024400 @default.
• W1007382022 hasConcept C144133560 @default.
• W1007382022 hasConcept C148043351 @default.
• W1007382022 hasConcept C149441793 @default.
• W1007382022 hasConcept C149782125 @default.
• W1007382022 hasConcept C149923435 @default.
• W1007382022 hasConcept C196083921 @default.
• W1007382022 hasConcept C199422724 @default.
• W1007382022 hasConcept C2781315470 @default.
• W1007382022 hasConcept C2908647359 @default.
• W1007382022 hasConcept C33923547 @default.
• W1007382022 hasConcept C41054675 @default.
• W1007382022 hasConceptScore W1007382022C105795698 @default.
• W1007382022 hasConceptScore W1007382022C114614502 @default.
• W1007382022 hasConceptScore W1007382022C119599485 @default.
• W1007382022 hasConceptScore W1007382022C121955636 @default.
• W1007382022 hasConceptScore W1007382022C127413603 @default.
• W1007382022 hasConceptScore W1007382022C129848803 @default.
• W1007382022 hasConceptScore W1007382022C144024400 @default.
• W1007382022 hasConceptScore W1007382022C144133560 @default.
• W1007382022 hasConceptScore W1007382022C148043351 @default.
• W1007382022 hasConceptScore W1007382022C149441793 @default.
• W1007382022 hasConceptScore W1007382022C149782125 @default.
• W1007382022 hasConceptScore W1007382022C149923435 @default.
• W1007382022 hasConceptScore W1007382022C196083921 @default.
• W1007382022 hasConceptScore W1007382022C199422724 @default.
• W1007382022 hasConceptScore W1007382022C2781315470 @default.
• W1007382022 hasConceptScore W1007382022C2908647359 @default.
• W1007382022 hasConceptScore W1007382022C33923547 @default.
• W1007382022 hasConceptScore W1007382022C41054675 @default.
• W1007382022 hasIssue "5" @default.
• W1007382022 hasLocation W10073820221 @default.
• W1007382022 hasOpenAccess W1007382022 @default.
• W1007382022 hasPrimaryLocation W10073820221 @default.
• W1007382022 hasRelatedWork W1007382022 @default.
• W1007382022 hasRelatedWork W1591394419 @default.
• W1007382022 hasRelatedWork W2006952761 @default.
• W1007382022 hasRelatedWork W2014698508 @default.
• W1007382022 hasRelatedWork W2023787198 @default.
• W1007382022 hasRelatedWork W2035140754 @default.
• W1007382022 hasRelatedWork W2079944649 @default.
• W1007382022 hasRelatedWork W2141530876 @default.

• next