Literature DB >> 9132904

Statistical power and design of focused clustering studies.

L A Waller1.   

Abstract

Focused clustering studies investigate raised incidence of disease in the vicinity of prespecified putative sources of increased risk. The analytic power functions of three focused tests of disease clustering are defined and used to address two design issues related to focused cluster studies. The power functions provide sample sizes required to detect a given increase in relative risk and allow measurement of the effects of aggregating data when a fixed underlying cluster model is assumed. Results are illustrated on hypothetical data as well as leukaemia data from upstate New York.

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Year:  1996        PMID: 9132904     DOI: 10.1002/(sici)1097-0258(19960415)15:7/9<765::aid-sim248>3.0.co;2-n

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


  13 in total

1.  Analyzing geographic patterns of disease incidence: rates of late-stage colorectal cancer in Iowa.

Authors:  Gerard Rushton; Ika Peleg; Aniruddha Banerjee; Geoffrey Smith; Michele West
Journal:  J Med Syst       Date:  2004-06       Impact factor: 4.460

2.  Spatial autocorrelation among automated geocoding errors and its effects on testing for disease clustering.

Authors:  Dale L Zimmerman; Jie Li; Xiangming Fang
Journal:  Stat Med       Date:  2010-01-19       Impact factor: 2.373

3.  The effects of local street network characteristics on the positional accuracy of automated geocoding for geographic health studies.

Authors:  Dale L Zimmerman; Jie Li
Journal:  Int J Health Geogr       Date:  2010-02-16       Impact factor: 3.918

4.  Power to detect spatial disturbances under different levels of geographic aggregation.

Authors:  Caroline Jeffery; A Ozonoff; Laura F White; Miriam Nuño; Marcello Pagano
Journal:  J Am Med Inform Assoc       Date:  2009-08-28       Impact factor: 4.497

5.  Power Evaluation of Focused Cluster Tests.

Authors:  Rc Puett; Ab Lawson; Ab Clark; Jr Hebert; M Kulldorff
Journal:  Environ Ecol Stat       Date:  2010-09       Impact factor: 1.119

6.  Modeling the probability distribution of positional errors incurred by residential address geocoding.

Authors:  Dale L Zimmerman; Xiangming Fang; Soumya Mazumdar; Gerard Rushton
Journal:  Int J Health Geogr       Date:  2007-01-10       Impact factor: 3.918

7.  Scale and shape issues in focused cluster power for count data.

Authors:  Robin C Puett; Andrew B Lawson; Allan B Clark; Tim E Aldrich; Dwayne E Porter; Charles E Feigley; James R Hebert
Journal:  Int J Health Geogr       Date:  2005-03-31       Impact factor: 3.918

8.  Error and bias in determining exposure potential of children at school locations using proximity-based GIS techniques.

Authors:  Paul A Zandbergen; Joseph W Green
Journal:  Environ Health Perspect       Date:  2007-09       Impact factor: 9.031

9.  Effect of spatial resolution on cluster detection: a simulation study.

Authors:  Al Ozonoff; Caroline Jeffery; Justin Manjourides; Laura Forsberg White; Marcello Pagano
Journal:  Int J Health Geogr       Date:  2007-11-27       Impact factor: 3.918

10.  Influence of geocoding quality on environmental exposure assessment of children living near high traffic roads.

Authors:  Paul A Zandbergen
Journal:  BMC Public Health       Date:  2007-03-16       Impact factor: 3.295

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