Matches in SemOpenAlex for { <https://semopenalex.org/work/W2019807152> ?p ?o ?g. }
Showing items 1 to 95 of
95
with 100 items per page.
- W2019807152 endingPage "1004" @default.
- W2019807152 startingPage "997" @default.
- W2019807152 abstract "This article is motivated by a lung cancer study where a regression model is involved and the response variable is too expensive to measure but the predictor variable can be measured easily with relatively negligible cost. This situation occurs quite often in medical studies, quantitative genetics, and ecological and environmental studies. In this article, by using the idea of ranked-set sampling (RSS), we develop sampling strategies that can reduce cost and increase efficiency of the regression analysis for the above-mentioned situation. The developed method is applied retrospectively to a lung cancer study. In the lung cancer study, the interest is to investigate the association between smoking status and three biomarkers: polyphenol DNA adducts, micronuclei, and sister chromatic exchanges. Optimal sampling schemes with different optimality criteria such as A-, D-, and integrated mean square error (IMSE)-optimality are considered in the application. With set size 10 in RSS, the improvement of the optimal schemes over simple random sampling (SRS) is great. For instance, by using the optimal scheme with IMSE-optimality, the IMSEs of the estimated regression functions for the three biomarkers are reduced to about half of those incurred by using SRS." @default.
- W2019807152 created "2016-06-24" @default.
- W2019807152 creator A5058388163 @default.
- W2019807152 creator A5073924559 @default.
- W2019807152 date "2004-12-01" @default.
- W2019807152 modified "2023-10-15" @default.
- W2019807152 title "Efficient Regression Analysis with Ranked-Set Sampling" @default.
- W2019807152 cites W1548728665 @default.
- W2019807152 cites W1619778662 @default.
- W2019807152 cites W1982307653 @default.
- W2019807152 cites W1983585864 @default.
- W2019807152 cites W1986049907 @default.
- W2019807152 cites W1995238259 @default.
- W2019807152 cites W1997505690 @default.
- W2019807152 cites W1997555727 @default.
- W2019807152 cites W2008408176 @default.
- W2019807152 cites W2017427896 @default.
- W2019807152 cites W2020195210 @default.
- W2019807152 cites W2026759867 @default.
- W2019807152 cites W2071957351 @default.
- W2019807152 cites W2073755149 @default.
- W2019807152 cites W2146876168 @default.
- W2019807152 cites W2277076748 @default.
- W2019807152 cites W2734557049 @default.
- W2019807152 doi "https://doi.org/10.1111/j.0006-341x.2004.00255.x" @default.
- W2019807152 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/15606420" @default.
- W2019807152 hasPublicationYear "2004" @default.
- W2019807152 type Work @default.
- W2019807152 sameAs 2019807152 @default.
- W2019807152 citedByCount "27" @default.
- W2019807152 countsByYear W20198071522012 @default.
- W2019807152 countsByYear W20198071522014 @default.
- W2019807152 countsByYear W20198071522015 @default.
- W2019807152 countsByYear W20198071522016 @default.
- W2019807152 countsByYear W20198071522017 @default.
- W2019807152 countsByYear W20198071522018 @default.
- W2019807152 countsByYear W20198071522020 @default.
- W2019807152 countsByYear W20198071522021 @default.
- W2019807152 crossrefType "journal-article" @default.
- W2019807152 hasAuthorship W2019807152A5058388163 @default.
- W2019807152 hasAuthorship W2019807152A5073924559 @default.
- W2019807152 hasConcept C105795698 @default.
- W2019807152 hasConcept C106131492 @default.
- W2019807152 hasConcept C111919701 @default.
- W2019807152 hasConcept C140779682 @default.
- W2019807152 hasConcept C152877465 @default.
- W2019807152 hasConcept C177264268 @default.
- W2019807152 hasConcept C199360897 @default.
- W2019807152 hasConcept C20353970 @default.
- W2019807152 hasConcept C2385561 @default.
- W2019807152 hasConcept C2908647359 @default.
- W2019807152 hasConcept C31972630 @default.
- W2019807152 hasConcept C33923547 @default.
- W2019807152 hasConcept C41008148 @default.
- W2019807152 hasConcept C71924100 @default.
- W2019807152 hasConcept C83546350 @default.
- W2019807152 hasConcept C99454951 @default.
- W2019807152 hasConceptScore W2019807152C105795698 @default.
- W2019807152 hasConceptScore W2019807152C106131492 @default.
- W2019807152 hasConceptScore W2019807152C111919701 @default.
- W2019807152 hasConceptScore W2019807152C140779682 @default.
- W2019807152 hasConceptScore W2019807152C152877465 @default.
- W2019807152 hasConceptScore W2019807152C177264268 @default.
- W2019807152 hasConceptScore W2019807152C199360897 @default.
- W2019807152 hasConceptScore W2019807152C20353970 @default.
- W2019807152 hasConceptScore W2019807152C2385561 @default.
- W2019807152 hasConceptScore W2019807152C2908647359 @default.
- W2019807152 hasConceptScore W2019807152C31972630 @default.
- W2019807152 hasConceptScore W2019807152C33923547 @default.
- W2019807152 hasConceptScore W2019807152C41008148 @default.
- W2019807152 hasConceptScore W2019807152C71924100 @default.
- W2019807152 hasConceptScore W2019807152C83546350 @default.
- W2019807152 hasConceptScore W2019807152C99454951 @default.
- W2019807152 hasIssue "4" @default.
- W2019807152 hasLocation W20198071521 @default.
- W2019807152 hasLocation W20198071522 @default.
- W2019807152 hasOpenAccess W2019807152 @default.
- W2019807152 hasPrimaryLocation W20198071521 @default.
- W2019807152 hasRelatedWork W1036777753 @default.
- W2019807152 hasRelatedWork W2088812990 @default.
- W2019807152 hasRelatedWork W2350399852 @default.
- W2019807152 hasRelatedWork W2370014976 @default.
- W2019807152 hasRelatedWork W2903368179 @default.
- W2019807152 hasRelatedWork W3047864323 @default.
- W2019807152 hasRelatedWork W336480102 @default.
- W2019807152 hasRelatedWork W4238714840 @default.
- W2019807152 hasRelatedWork W4379210352 @default.
- W2019807152 hasRelatedWork W4380302443 @default.
- W2019807152 hasVolume "60" @default.
- W2019807152 isParatext "false" @default.
- W2019807152 isRetracted "false" @default.
- W2019807152 magId "2019807152" @default.
- W2019807152 workType "article" @default.