Scientific Concept of the National Cohort (status ... - Nationale Kohorte

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C.2 C.2 Annex: Methods for Statistical Power and Sample Size Calculations Standardized difference corresponding to odds ratio OR [Q4-Q1] 1.5 1.6 1.7 1.8 1.9 2.0 power with repeats initial power power with repeats initial power power with repeats initial power power with repeats initial power power with repeats initial power power with repeats initial power Correlation between measured and true exposure rho(m,t) Correlation between repeat measurements rho(m1,m2) Number of cases 0.40 0.63 0.37 0.46 0.47 0.58 0.56 0.68 0.65 0.77 0.73 0.84 0.79 0.89 0.50 0.71 0.44 0.53 0.56 0.65 0.66 0.76 0.75 0.84 0.82 0.89 0.87 0.93 0.60 0.77 0.51 0.58 0.63 0.71 0.74 0.81 0.82 0.88 0.88 0.93 0.92 0.96 0.70 0.84 0.57 0.63 0.70 0.75 0.80 0.85 0.87 0.91 0.92 0.95 0.96 0.97 700 0.10 0.32 0.16 0.23 0.20 0.29 0.24 0.36 0.28 0.42 0.33 0.49 0.37 0.55 0.20 0.45 0.27 0.38 0.35 0.49 0.43 0.59 0.50 0.67 0.57 0.75 0.64 0.81 0.30 0.55 0.38 0.50 0.49 0.63 0.59 0.73 0.67 0.81 0.75 0.88 0.81 0.92 0.40 0.63 0.48 0.60 0.60 0.72 0.71 0.82 0.79 0.89 0.86 0.94 0.91 0.96 286 0.50 0.71 0.57 0.67 0.70 0.79 0.80 0.88 0.87 0.94 0.92 0.97 0.96 0.98 0.60 0.77 0.65 0.73 0.78 0.84 0.87 0.92 0.93 0.96 0.96 0.98 0.98 0.99 0.70 0.84 0.72 0.77 0.84 0.88 0.91 0.94 0.96 0.97 0.98 0.99 0.99 1.00 1000 0.10 0.32 0.21 0.31 0.26 0.39 0.32 0.48 0.38 0.56 0.44 0.64 0.50 0.70 0.20 0.45 0.37 0.51 0.47 0.63 0.56 0.74 0.65 0.82 0.73 0.88 0.79 0.92 0.30 0.55 0.51 0.65 0.63 0.78 0.74 0.87 0.82 0.93 0.88 0.96 0.92 0.98 0.40 0.63 0.63 0.75 0.76 0.86 0.85 0.93 0.91 0.97 0.95 0.99 0.98 0.99 0.50 0.71 0.73 0.82 0.84 0.91 0.92 0.96 0.96 0.99 0.98 1.00 0.99 1.00 0.60 0.77 0.80 0.86 0.90 0.94 0.96 0.98 0.98 0.99 0.99 1.00 1.00 1.00 0.70 0.84 0.86 0.90 0.94 0.96 0.98 0.99 0.99 1.00 1.00 1.00 1.00 1.00
C.3 References 287 References 1. RKI, Health in Germany/Gesundheit in Deutschland. Robert Koch Institut, 2007(ISBN 3-89606-173-9). 2. Van Baal, P., et al., Lifetime medical costs of obesity: prevention no cure for increasing health expenditure. PLoS Med, 2008. 5(2): p. e29. 3. Rappange, D., et al., Lifestyle intervention: from cost savings to value for money. Journal of Public Health, 2010. 32(3): p. 440. 4. Razum, O., et al., Social Epidemiology after the German Reunification: East vs. West or Poor vs. Rich? International Journal of Public Health, 2008. 53(1): p. 13- 22. 5. Holford, T. and C. Stack, Study design for epidemiologic studies with measurement error. Statistical Methods in Medical Research, 1995. 4(4): p. 339. 6. White, E., J. Hunt, and D. Casso, Exposure measurement in cohort studies: the challenges of prospective data collection. Epidemiologic reviews, 1998. 20(1): p. 43. 7. Anderson, G.L., et al., Assessing Lead Time of Selected Ovarian Cancer Biomarkers: A Nested Case–Control Study. Journal of the National Cancer Institute, 2010. 102(1): p. 26-38. 8. Muller-Nordhorn, J., et al., Regional variation and time trends in mortality from ischaemic heart disease: East and West Germany 10 years after reunification. British Medical Journal, 2004. 58(6): p. 481. 9. Klapper, A., D. Bardehle, and O. Razum, Alters-und geschlechtsspezifische Mortalität im Ruhrgebiet von 1994 bis 2004 [Age-and sex-specific mortality in the Ruhr region from 1994 to 2004]. Das Gesundheitswesen, 2007. 69(10): p. 521– 526. 10. Dragano, N., et al., Subclinical coronary atherosclerosis and neighbourhood deprivation in an urban region. European journal of epidemiology, 2009. 24(1): p. 25-35. 11. Dragano, N., et al., Neighbourhood socioeconomic status and cardiovascular risk factors: a multilevel analysis of nine cities in the Czech Republic and Germany. BMC Public Health, 2007. 7(1): p. 255. 12. Ouzounian, M., et al., Predict, prevent and personalize: Genomic and proteomic approaches to cardiovascular medicine. The Canadian journal of cardiology, 2007. 23(Suppl A): p. 28A. 13. Dent, T.H.S., Predicting the risk of coronary heart disease: I. The use of conventional risk markers. Atherosclerosis, 2010. 213(2): p. 345-351. 14. Dent, T.H.S., Predicting the risk of coronary heart disease. II: The role of novel molecular biomarkers and genetics in estimating risk, and the future of risk prediction. Atherosclerosis, 2010. 213(2): p. 352-362. 15. Wilson, P., et al., Prediction of coronary heart disease using risk factor categories. Circulation, 1998. 97(18): p. 1837. 16. Conroy, R., et al., Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. European heart journal, 2003. 24(11): p. 987. C.3
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The National Cohort A prospective e
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Applicants Applicants Applicants Cl
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Applicants IV
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Executive Summary 2. The National C
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Executive Summary 3. Scientific aim
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Executive Summary essary to address
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Executive Summary 7. Examples for s
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Contents A.2.4 major areas of expos
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Contents A.3.8.2 Social security da
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Contents A.6.4.2 Minimally detectab
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Abbreviations C.2 mEThOdS fOr STATI
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Abbreviations DXA Dual-energy x-ray
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Abbreviations CHS Cardiovascular He
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A.1 A.1 Introduction and overview a
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A.1 A.1 Introduction and overview s
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A.3 A.3 Study design depression and
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A.3 A.3 Study design ticipants and
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A.3 A.3 Study design a resting time
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A.3 A.3 Study design index, convent
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A.3 A.3 Study design 6. Since being
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A.3 A.3 Study design A.3.5 Collecti
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A.3 A.3 Study design study. For exa
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Page 326 and 327: C.3 References 526. Mack, F., et al
Page 328 and 329: C.3 References 560. Palatini, P., A
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