Two-stage method to remove population- and individual-level outliers from longitudinal data in a primary care database

Pharmacoepidemiology and Drug Safety

Volumn 21, Issue 7, 2012, Pages 725-732

  Welch, C ^a   Petersen, I ^a   Walters, K ^a   Morris, R W ^a   Nazareth, I ^a,b   Kalaitzaki, E ^b   White, I R ^c   Marston, L ^a   Carpenter, J ^d  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b MEDICAL RESEARCH COUNCIL   (United Kingdom)

^c UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^d LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

Author keywords

Longitudinal data; Outliers; Primary care database

Indexed keywords

ARTICLE; BODY HEIGHT; CLINICAL PRACTICE; DATA BASE; HEALTH SURVEY; HUMAN; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; METHODOLOGY; PRIMARY MEDICAL CARE; PRIORITY JOURNAL;

EID: 84863551824     PISSN: 10538569     EISSN: 10991557     Source Type: Journal    
DOI: 10.1002/pds.2270     Document Type: Article

References (16)

1. Dixon WJ. Analysis of Extreme Values. Ann. Math. Stat. 1950; 21: 488-506.
2. Bourke A, Dattani H, Robinson M. Feasibility Study and Methodology to Create a Quality-Evaluated Database of Primary Care Data. Inform. Prim. Care 2004; 12: 171-177.
3. Maguire A, Blak BT, Thompson M. The Importance of Defining Periods of Complete Mortality Reporting for Research Using Automated Data From Primary Care. Pharmacoepidemiol. Drug Saf 2009; 18: 76-83.
4. Health Survey for England 1cf5E. National Centre for Social Research and University College London. Department of Epidemiology and Public Health. 2010. Colchester, Essex, UK Data Archive [distributor]. Ref Type: Data File.
5. National Centre for Social Research and University College London. Department of Epidemiology and Public Health. Health Survey for England, 2008 [computer file] 2nd Edition. 2010. Colchester, Essex, UK Data Archive [distributer]. Ref Type: Data File.
6. Anscombe FJ. Rejection of Outliers. Biometrics 1959; 15: 632-632.
7. Sorkin JD, Muller DC, Andres R. Longitudinal Change in Height of Men and Women: Implications for Interpretation of the Body Mass Index: the Baltimore Longitudinal Study of Aging. Am. J. Epidemiol. 1999; 150: 969-977.
8. Healy MJ. Outliers in Clinical Chemistry Quality-Control Schemes. Clin. Chem. 1979; 25: 675-677.
9. Hayes K, Kinsella A, Coffey N. A Note on the Use of Outlier Criteria in Ontario Laboratory Quality Control Schemes. Clin. Biochem. 2007; 40: 147-152.
10. Horn PS, Feng L, Li Y, et al. Effect of Outliers and Nonhealthy Individuals on Reference Interval Estimation. Clin. Chem. 2001; 47: 2137-2145.
11. Motulsky HJ, Brown RE. Detecting Outliers When Fitting Data With Nonlinear Regression-a New Method Based on Robust Nonlinear Regression and the False Discovery Rate. BMC Bioinforma. 2006; 7: 123.
12. McClure FD, Lee JK, Wilson DB. Validity of the Percent Reduction in Standard Deviation Outlier Test for Screening Laboratory Means From a Collaborative Study. J. AOAC Int. 2003; 86: 1045-1055.
13. Verardi V, Dehon C. Multivariate Outlier Detection in Stata. Stata J. 2010; 10: 259-266.
14. Chang LC, Jones DK, Pierpaoli C. RESTORE: Robust Estimation of Tensors by Outlier Rejection. Magn. Reson. Med. 2005; 53: 1088-1095.
15. Chen D, Shao X, Hu B, et al. Simultaneous Wavelength Selection and Outlier Detection in Multivariate Regression of Near-Infrared Spectra. Anal. Sci. 2005; 21: 161-166.
16. Clarke R, Shipley M, Lewington S, et al. Underestimation of Risk Associations Due to Regression Dilution in Long-Term Follow-Up of Prospective Studies. Am. J. Epidemiol. 1999; 150: 341-353.