Literature DB >> 3589249

An approximation for the distribution of the scan statistic.

S Wallenstein, N Neff.   

Abstract

The scan statistic evaluates whether an apparent cluster of disease in time is due to chance. The statistic employs a 'moving window' of length w and finds the maximum number of cases revealed through the window as it scans or slides over the entire time period T. Computation of the probability of observing a certain size cluster, under the hypothesis of a uniform distribution, is infeasible when N, the total number of events, is large, and w is of moderate or small size relative to T. We give an approximation that is an asymptotic upper bound, easy to compute, and, for the purposes of hypothesis testing, more accurate than other approximations presented in the literature. The approximation applies both when N is fixed, and when N has a Poisson distribution. We illustrate the procedure on a data set of trisomic spontaneous abortions observed in a two year period in New York City.

Mesh:

Year:  1987        PMID: 3589249     DOI: 10.1002/sim.4780060212

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  11 in total

1.  Identification of chromosomal translocation hotspots via scan statistics.

Authors:  Israel T Silva; Rafael A Rosales; Adriano J Holanda; Michel C Nussenzweig; Mila Jankovic
Journal:  Bioinformatics       Date:  2014-05-23       Impact factor: 6.937

2.  Mapping tumor-suppressor genes with multipoint statistics from copy-number-variation data.

Authors:  Iuliana Ionita; Raoul-Sam Daruwala; Bud Mishra
Journal:  Am J Hum Genet       Date:  2006-05-30       Impact factor: 11.025

3.  A negative feedback loop of transcription factors specifies alternative dendritic cell chromatin States.

Authors:  Chamutal Bornstein; Deborah Winter; Zohar Barnett-Itzhaki; Eyal David; Sabah Kadri; Manuel Garber; Ido Amit
Journal:  Mol Cell       Date:  2014-11-20       Impact factor: 17.970

4.  Detection of excessive activities in time series of graphs.

Authors:  Suchismita Goswami; Edward J Wegman
Journal:  J Appl Stat       Date:  2019-06-28       Impact factor: 1.416

5.  Whole-genome detection of disease-associated deletions or excess homozygosity in a case-control study of rheumatoid arthritis.

Authors:  Chih-Chieh Wu; Sanjay Shete; Eun-Ji Jo; Yaji Xu; Emily Y Lu; Wei V Chen; Christopher I Amos
Journal:  Hum Mol Genet       Date:  2012-12-06       Impact factor: 6.150

6.  Epicardial mapping of ventricular fibrillation over the posterior descending artery and left posterior papillary muscle of the swine heart.

Authors:  Thomas D Nielsen; Jian Huang; Jack M Rogers; Cheryl R Killingsworth; Raymond E Ideker
Journal:  J Interv Card Electrophysiol       Date:  2008-10-07       Impact factor: 1.900

7.  Detection of disease-associated deletions in case-control studies using SNP genotypes with application to rheumatoid arthritis.

Authors:  Chih-Chieh Wu; Sanjay Shete; Wei V Chen; Bo Peng; Annette T Lee; Jianzhong Ma; Peter K Gregersen; Christopher I Amos
Journal:  Hum Genet       Date:  2009-05-05       Impact factor: 4.132

8.  Scan-statistic approach identifies clusters of rare disease variants in LRP2, a gene linked and associated with autism spectrum disorders, in three datasets.

Authors:  Iuliana Ionita-Laza; Vlad Makarov; Joseph D Buxbaum
Journal:  Am J Hum Genet       Date:  2012-05-10       Impact factor: 11.025

9.  Automated DNA sequence-based early warning system for the detection of methicillin-resistant Staphylococcus aureus outbreaks.

Authors:  Alexander Mellmann; Alexander W Friedrich; Nicole Rosenkötter; Jörg Rothgänger; Helge Karch; Ralf Reintjes; Dag Harmsen
Journal:  PLoS Med       Date:  2006-03       Impact factor: 11.069

10.  Assessing current temporal and space-time anomalies of disease incidence.

Authors:  Chih-Chieh Wu; Chien-Hsiun Chen; Sanjay Shete
Journal:  PLoS One       Date:  2017-11-13       Impact factor: 3.240

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