유전체 코호트 연구의 주요 통계학적 과제

참고문헌 (24)

1. Hunter DJ, "Cohort studies of fat intake and the risk of breast cancer-a pooled analysis", 334(6), pp.356~361 (1996)
2. Prentice RL, "Measurement error and results from analytic epidemiology: Dietary fat and breast cancer", 88(23), pp.1738~1747 (1996)
3. Fuchs CS, "Dietary fiber and the risk of colorectal cancer and adenoma in women", 340(3), pp.169~176 (1999)
4. Park Y, "Dietary fiber intake and risk of colorectal cancer: A pooled analysis of prospective cohort studies", 294(22), pp.2849~2857 (2005)
5. Fraser GE, "Regression calibration in studies with correlated variables measured with error", 154(9), pp.836~844 (2001)
6. Thomas D, "New techniques for the analysis of cohort studies", 20(1), pp.122~134 (1998)
7. Rosner B, "Willett WC. Correction of logistic regression relative risk estimates and confidence intervals for measurement error The case of multiple covariates measured with error. Am J Epidemiol 1990", pp.734~745
8. Rosner B, "Spiegelman D. Correction of logistic regression relative risk estimates and confidence intervals for systematic withinperson measurement error. Stat Med 1989", pp.1051~1069
9. "Gray R. Cost-efficient study designs for binary response data with Gaussian covariate measurement error. Biometrics 1991", pp.851~869
10. Park S, "Cost-efficient design of main cohort and calibration studies where one or more exposure variables are measured with errors", 11(15), pp.2611~2616 (2002), New York, NY
11. Hauser R, "Temporal variability of urinary phthalate metabolite levels in men of reproductive age", 112(17), pp.1734~1740 (2004)
12. Park S, "A latent model for measurement error correction using replicate data", 20(23), pp.273~ (2005)
13. Carroll RJ, "Measurement Error in Nonlinear Models", pp.141~164 (1995), New York: Chapman and Hall
14. "Rothman K. No adjustments are needed for multiple comparisons. Epidemiology 1990", pp.43~46
15. Weinberg CR, "It's time to rehabilitate the pvalue", 12(3), pp.288~290 (2001)
16. Benjamini Y, "Controlling the false discovery rate: a practical and powerful approach to multiple testing", 57(1), pp.289~300 (1995)
17. Wacholder S, "Assessing the probability that a positive report is false: An approach for molecular epidemiology studies", 96(6), pp.434~442 (2004)
18. Breslow NE, "Day NE. Statistical methods in cancer research. Volume II--The design and analysis of cohort studies. IARC Sci Publ 1987", pp.1~406
19. Ritchie MD, "Multifactordimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer", 69(1), pp.138~147 (2001)
20. Motsinger AA, "Multifactor dimensionality reduction: an analysis strategy for modelling and detecting gene-gene interactions in human genetics and pharmacogenomics studies", 2(5), pp.318~328 (2006)
21. Ritchie MD, "Power of multifactor dimensionality reduction for detecting gene-gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity", 24(2), pp.150~157 (2003)
22. Chen J, "A partially linear tree-based regression model for assessing complex joint gene-gene and geneenvironment effects" (2007)
23. Prentice RL, "Statistical issues arising in the Women's Health Initiative", 61(4), pp.899~911 (2005)
24. Carlin B, "Bayes and Empirical- Bayes Methods for Data Analysis. 2nd ed", pp.57~85 (2000), New York: Chapman and Hall