PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 11836732

Score tests for detecting excess risks around putative sources.

Toshiro Tango
View original source ↗Export metadata ↓

Abstract

Focused clustering studies examine raised disease risk around prespecified point sources. As statistical methods to detect such clusters, Stone's maximum likelihood ratio test is popular, against the general ordered alternatives and score tests which score each case the reciprocal of the distance from a point source as a surrogate exposure. This paper considers extensions of score tests in that (i) they can allow us to select the best among prespecified parametric exposure functions to avoid multiple testing problems and (ii) they can be applied to a possible situation where the hazardous substance levels have a peak at some distance from a point source. Simulation studies show that the powers of the proposed tests are higher than that of Stone's test over all the alternatives considered. The proposed tests are illustrated with hypothetical data as well as simulated data to be expected in an epidemiological study currently in progress regarding an excess risk of perinatal undesirable outcomes near municipal solid waste incinerators in Japan.

Explore related subjects

Cluster AnalysisEnvironmental ExposureFemaleHumansIncinerationInfant, NewbornJapanMalePregnancyRefuse DisposalRiskStatistics as TopicComparative StudyJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Toshiro Tango. 2002-02-28. Score tests for detecting excess risks around putative sources.. https://doi.org/10.1002/sim.1003

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2025

Clustering individuals using INMTD: a novel versatile multi-view embedding framework integrating omics and imaging data.

MOTIVATION: Combining omics and images can lead to a more comprehensive clustering of individuals than classic single-view approaches. Among the various approaches for multi-view clustering, nonnegative matrix tri-factorization (NMTF) and nonnegative Tucker decomposition (NTD) are advantageous in learning low-rank embeddings with promising interpretability. Besides, there is a need to handle unwanted drivers of clusterings (i.e. confounders). RESULTS: In this work, we introduce a novel multi-view clustering method based on NMTF and NTD, named INMTD, which integrates omics and 3D imaging data to derive unconfounded subgroups of individuals. According to the adjusted Rand index, INMTD outperformed other clustering methods on a synthetic dataset with known clusters. In the application to real-life facial-genomic data, INMTD generated biologically relevant embeddings for individuals, genetics, and facial morphology. By removing confounded embedding vectors, we derived an unconfounded clustering with better internal and external quality; the genetic and facial annotations of each derived subgroup highlighted distinctive characteristics. In conclusion, INMTD can effectively integrate omics data and 3D images for unconfounded clustering with biologically meaningful interpretation. AVAILABILITY AND IMPLEMENTATION: INMTD is freely available at https://github.com/ZuqiLi/INMTD.

Cluster Analysis↗
PubMed2006

Inbreeding and surnames: a projection into Easter Island's past.

The population of Easter Island is one of the most interesting extant human communities due to its unique demographic history, its geographic isolation, and the development of an incomparable culture characterized by the towering "Moais" and its enigmatic writing. Following the colonization of its population by Polynesians from the Mangarevan Islands in the 5th century AD, the island remained isolated up until the middle of the 20th century. Under these conditions, with endogamy levels fluctuating between 61.04-96.54% and given such a small population, a high rate of inbreeding, and consequently, an elevated level of genetic relationships would be expected. Using data from church and civil records, we calculated the consanguinity of the population of Rapa Nui. The results of this analysis do not support the hypothesis of a high level of consanguinity (alpha = 0.00028 and F(t) = 0.0007, with F(r) = 0.00586 and F(n) = -0.00519), suggesting instead the existence of a strategy used to avoid marriage between close relatives. To explain these observations, the structure and exchange dynamics of the population were studied in the tribes, known locally as "Mata." The results of this analysis suggest a tendency toward the avoidance of inbreeding within tribes, in order to decrease the rate of endogamy in each group. This is consistent with ethnographic observations from the beginning of the 20th century that support the existence of strict regulations to prevent inbreeding between closely related individuals. Furthermore, we confirm that this situation dates back to a period before the "refounding" of Easter Island. Our results demonstrate that conditions of geographical isolation are not in themselves sufficient to produce an elevated inbreeding coefficient, revealing Easter Island as an interesting example of how cultural rules can shape the genetic structure of a population.

Cluster Analysis↗