Detection of outliers due to participants' non-adherence to protocol in a longitudinal study of cognitive decline

PLoS ONE

Volumn 10, Issue 7, 2015, Pages

  Dugravot, Aline ^a,b   Sabia, Severine ^a,c,d   Shipley, Martin J ^c   Welch, Catherine ^c   Kivimaki, Mika ^c   Singh Manoux, Archana ^a,b,c  

^a CENTRE FOR RESEARCH IN EPIDEMIOLOGY AND POPULATION HEALTH   (France)

^b UNIVERSITÉ PARIS SACLAY   (France)

^c UNIVERSITY COLLEGE LONDON   (United Kingdom)

^d LABORATOIRE DES SCIENCES DU CLIMAT ET DE L ENVIRONNEMENT   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGE; AGED; ARTICLE; COGNITION; COGNITIVE BIAS; COGNITIVE DEFECT; CONTROLLED STUDY; DIABETES MELLITUS; DISEASE ASSOCIATION; FEMALE; HUMAN; LONGITUDINAL STUDY; MALE; MEASUREMENT ERROR; OUTLIER; PREDICTION; PROTOCOL COMPLIANCE; PROTOCOL NONADHERENCE; RISK FACTOR; COGNITION DISORDERS; MIDDLE AGED; NEUROPSYCHOLOGICAL TEST; PATIENT COMPLIANCE; PSYCHOLOGY;

ADULT; COGNITION; COGNITION DISORDERS; FEMALE; HUMANS; LONGITUDINAL STUDIES; MALE; MIDDLE AGED; NEUROPSYCHOLOGICAL TESTS; PATIENT COMPLIANCE; RISK FACTORS;

EID: 84941364312     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0132110     Document Type: Article

References (34)

1. Dodd S, White IR, Williamson P. (2012) Nonadherence to treatment protocol in published randomised controlled trials: a review. Trials 13: 84. doi: 10.1186/1745-6215-13-84 PMID: 22709676
2. Fergusson D, Aaron SD, Guyatt G, Hebert P. (2002) Post-randomisation exclusions: the intention to treat principle and excluding patients from analysis. BMJ (Clinical research ed 325: 652-654. PMID: 12242181
3. Grubbs FE. (1969) Procedures for detecting outlying obesrvations in samples. Technometrics 11: 1-21.
4. Motulsky HJ, Brown RE. (2006) Detecting outliers when fitting data with nonlinear regression-a new method based on robust nonlinear regression and the false discovery rate. BMC Bioinformatics 7: 123. PMID: 16526949
5. McClure FD, Lee JK, Wilson DB. (2003) Validity of the percent reduction in standard deviation outlier test for screening laboratory means from a collaborative study. J AOAC Int 86: 1045-1055. PMID: 14632408
6. Dixon WJ. (1950) Analysis of extreme vlaues. The Annals of Mathematical Statistics 21: 488-506.
7. Welch C, Petersen I, Walters K, Morris RW, Nazareth I, et al. (2012) Two-stage method to remove population- and individual-level outliers from longitudinal data in a primary care database. Pharmacoepidemiol Drug Saf 21: 725-732. doi: 10.1002/pds.2270 PMID: 22052713
8. Diggle P, Heagerty P, Liang K-Y, Zeger S (2002) Analysis of longitudinal data. 2nd ed. ed. Oxford: OUP.
9. Marmot M, Brunner E. (2005) Cohort Profile: the Whitehall II study. Int J Epidemiol 34: 251-256. PMID: 15576467
10. Heim AW (1970) AH 4 group test of general Intelligence. Windsor, UK: NFER-Nelson Publishing Company Ltd.
11. Raven JC (1965) Guide to using the Mill Hill vocabulary test with progressive matrices. London, UK: HK Lewis.
12. Borkowski JG, Benton AL, Spreen O. (1967) Word fluency and brain damage. Neuropsychologica 5: 135-140.
13. Folstein MF, Folstein SE, McHugh PR. (1975) "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12: 189-198. PMID: 1202204
14. Bowie CR, Harvey PD. (2006) Administration and interpretation of the Trail Making Test. Nat Protoc 1: 2277-2281. PMID: 17406468
15. Singh-Manoux A, Marmot MG, Glymour M, Sabia S, Kivimaki M, et al. (2011) Does cognitive reserve shape cognitive decline? Ann Neurol 70: 296-304. doi: 10.1002/ana.22391 PMID: 21563209
16. Solomon A, Mangialasche F, Richard E, Andrieu S, Bennett DA, et al. (2014) Advances in the prevention of Alzheimer's disease and dementia. J Intern Med 275: 229-250. doi: 10.1111/joim.12178 PMID: 24605807
17. Stern Y. (2002) What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc 8: 448-460. PMID: 11939702
18. Barnes DE, Yaffe K. (2011) The projected effect of risk factor reduction on Alzheimer's disease prevalence. Lancet Neurol 10: 819-828. doi: 10.1016/S1474-4422(11)70072-2 PMID: 21775213
19. Sabia S, Nabi H, Kivimaki M, Shipley MJ, Marmot MG, et al. (2009) Health behaviors from early to late midlife as predictors of cognitive function: The Whitehall II study. Am J Epidemiol 170: 428-437. doi: 10.1093/aje/kwp161 PMID: 19574344
20. Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Bassett DR Jr., et al. (2011) 2011 Compendium of Physical Activities: a second update of codes and MET values. Med Sci Sports Exerc 43: 1575-1581. doi: 10.1249/MSS.0b013e31821ece12 PMID: 21681120
21. Kaffashian S, Dugravot A, Nabi H, Batty GD, Brunner E, et al. (2011) Predictive utility of the Framingham general cardiovascular disease risk profile for cognitive function: evidence from the Whitehall II study. Eur Heart J 32: 2326-2332. doi: 10.1093/eurheartj/ehr133 PMID: 21606085
22. Singh-Manoux A, Britton AR, Marmot M. (2003) Vascular disease and cognitive function: evidence from the Whitehall II Study. J Am Geriatr Soc 51: 1445-1450. PMID: 14511166
23. Singh-Manoux A, Sabia S, Lajnef M, Ferrie JE, Nabi H, et al. (2008) History of coronary heart disease and cognitive performance in midlife: the Whitehall II study. Eur Heart J 29: 2100-2107. doi: 10.1093/ eurheartj/ehn298 PMID: 18648106
24. Jokela M, Singh-Manoux A, Ferrie JE, Gimeno D, Akbaraly TN, et al. (2010) The association of cognitive performance with mental health and physical functioning strengthens with age: the Whitehall II cohort study. Psychol Med 40: 837-845. doi: 10.1017/S0033291709991024 PMID: 19719898
25. Singh-Manoux A, Akbaraly TN, Marmot M, Melchior M, Ankri J, et al. (2010) Persistent depressive symptoms and cognitive function in late midlife: the Whitehall II study. J Clin Psychiatry 71: 1379-1385. doi: 10.4088/JCP.09m05349gry PMID: 20584520
26. The Expert Committee on the Diagnosis and Classification of Diabetes. (1997) Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 20: 1183-1197. PMID: 9203460
27. Ferrie JE, Langenberg C, Shipley MJ, Marmot MG. (2006) Birth weight, components of height and coronary heart disease: evidence from the Whitehall II study. Int J Epidemiol 35: 1532-1542. PMID: 16931524
28. Britton A, Milne B, Butler T, Sanchez-Galvez A, Shipley M, et al. (2012) Validating self-reported strokes in a longitudinal UK cohort study (Whitehall II): Extracting information from hospital medical records versus the Hospital Episode Statistics database. BMC Med Res Methodol 12: 83. doi: 10.1186/1471- 2288-12-83 PMID: 22720999
29. Ware JE, Snow KK, Kosinski M (1993) SF-36 health Survey: manual and interpretation guide. Boston MA: The Health Institute, New England Medical Centre.
30. Watson R, Deary IJ, Shipley B. (2008) A hierarchy of distress: Mokken scaling of the GHQ-30. Psychol Med 38: 575-579. doi: 10.1017/S003329170800281X PMID: 18226289
31. Rabbitt P, Diggle P, Smith D, Holland F, Mc IL. (2001) Identifying and separating the effects of practice and of cognitive ageing during a large longitudinal study of elderly community residents. Neuropsychologia 39: 532-543. PMID: 11254936
32. Fitzmaurice GM, Laird NM, Ware JH (2004) Applied longitudinal analysis. Hoboken, New Jersey
33. Ferrer E, Salthouse TA, Stewart WF, Schwartz BS. (2004) Modeling age and retest processes in longitudinal studies of cognitive abilities. Psychol Aging 19: 243-259. PMID: 15222818
34. Rabbitt P, Lunn M, Wong D, Cobain M. (2008) Age and ability affect practice gains in longitudinal studies of cognitive change. J Gerontol B Psychol Sci Soc Sci 63: 235-240.