Last updated: 9/1/2011 [PDF]
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Chapters 1-10 [PDF]
Taubes G. Do we really know what makes us healthy? New York Times. New York, 2007. [PDF]
Lehrer J. The truth wears off. The New Yorker. New York, 2010. [PDF]
* Hernan MA. Invited commentary: hypothetical interventions to define causal effects--afterthought or prerequisite? Am J Epidemiol 2005;162:618-20; discussion 621-2. [PDF]
* Kaufman JS, Cooper RS. Seeking Causal Explanations in Social Epidemiology. American Journal of Epidemiology 1999;150:113-120. [PDF]
Little RJ, Rubin DB. Causal effects in clinical and epidemiological studies via potential outcomes: concepts and analytical approaches. Annu Rev Public Health 2000;21:121-45. [PDF]
Dawid AP. Counterfactuals: help or hindrance? Int J Epidemiol 2002;31:429-30. [PDF] [Note this paper starts after Maldonado's paper]
* Maldonado G, Greenland S. Estimating causal effects. Int J Epidemiol 2002;31:422-38. [PDF]
* Holland PW. Statistics and Causal Inference. Journal of the American Statistical Association 1986;91:945-960. [PDF]
Rosenbaum PR. From Association to Causation in Observational Studies: The Role of Tests of Strongly Ignorable Treatment Assignment. J Am Stat Assoc 1984;79:41-48. [PDF]
Greenland S, Robins JM. Identifiability, exchangeability, and epidemiological confounding. Int J Epidemiol 1986;15:413-9. [PDF]
Greenland S, Robins JM. Identifiability, exchangeability and confounding revisited. Epidemiol Perspect Innov 2009;6(1):4 [PDF] [HTML]
* Oakes JM, Johnson PJ. Propensity score matching methods for social epidemiology. Pp. 370-392 in Methods in Social Epidemiology, Oakes JM, Kaufman JS, eds. San Francisco: Jossey-Bass, 2006 [PDF]
* Becher H. The concept of residual confounding in regression models and some applications. Stat Med 1992;11:1747-58. [PDF]
* Manski CF. Identification problems in the social sciences and everyday life. Southern Economic Journal 2003;70:11-21. [PDF]
Robins JM. Data, design, and background knowledge in etiologic inference. Epidemiology 2001;12:313-320. [PDF]
Greenland S, Morgenstern H. Confounding in health research. Annu Rev Public Health 2001;22:189-212. [PDF]
Hernan MA, Hernandez-Diaz S, Werler MM, Mitchell AA. Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology. Am J Epideiol 2002;155:176-84. [PDF]
*Hernan MA, Clayton D, Keiding N. The Simpson's paradox unraveled. Int J Epidemiol 2011;40:780-5. [PDF]
*Cole SR, Platt RW, Schisterman EF, Chu H, Westreich D, Richardson D, Poole C. Illustrating bias due to conditioning on a collider. Int J Epidemiol 2010;39:417-20. [PDF]
Dosemeci M, Wacholder S, Lubin JH. Does nondifferential misclassification of exposure always bias a true effect toward the null value? Am J Epidemiol 1990;132:746-8. [PDF]
* Flegal KM, Keyl PM, Nieto FJ. Differential misclassification arising from nondifferential errors in exposure measurement. Am J Epidemiol 1991;134:1233-44. [PDF]
* Jurek AM, Greenland S, Maldonado G, Church T. Proper interpretation of non-differential misclassification effects: expectations vs. observations. Int J Epidemiol 2005;34:680-7. [PDF]
Greenland S. Basic problems in interaction assessment. Environ Health Perspect 1993:101 Suppl 4:59-66. [PDF]
* VanderWeele TJ. Sufficient cause interactions and statistical interactions. Epidemiology 2009;20:6-13. [PDF]
Robins JM, Greenland S. Identifiability and exchangeability for direct and indirect effects. Epidemiology 1992:3:143-55. [PDF]
Cole SR, Hernan MA. Fallibility in estimating direct effects. Int J Epidemiol 2002;31:163-5. [PDF]
Kaufman JS, Maclehose RF, Kaufman S. A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation. Epidemiol Perspect Innov 2004;1:4 [PDF]
Poole C. Low P-values or narrow confidence intervals: which are more durable? Epidemiology 2001;12:291-4. [PDF]
Rothman KJ. Curbing type I and type II errors. Eur J Epidemiol 2010;25:223-4. [PDF]
Stang A, Poole C, Kuss O. The ongoing tyranny of statistical significance testing in biomedical research. Eur J Epidemiol 2010;25:225-30. [PDF]
Goodman S. A dirty dozen: twelve p-value misconceptions. Semin Hematol 2008;45:135-40. [PDF]
* Hoenig JM, Heisey DM. The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis. The American Statistician 2001;55:19-24. [PDF]
* Oakes JM. Statistical Power and Sample Size: Considerations for Clinician-Researchers. in Essentials of Clinical Research, edited by Stephen P Glasser. New York: Springer. In press [PDF]
* Savitz DA, Tolo KA, Poole C. Statistical significance testing in the American Journal of Epidemiology, 1970-1990. Am J Epidemiol 1994;139:1047-52. [PDF]
Glymour MM. Natural experiments and instrumental variable analyses in social epidemiology. In: Methods in Social Epidemiology, Oakes JM, Kaufman JS, eds. San Francisco: Jossey-Bass / Wiley, 2006:423-445. [PDF]
Hernan MA, Robins JM. Instruments for causal inference: an epidemiologist's dream? Epidemiology 2006;17:360-72. [PDF]
Greenland S. Bayesian perspectives for epidemiological research: I. Foundations and basic methods. Int J Epidemiol 2006;35:765-75 [PDF]
Greenland S. Bayesian perspectives for epidemiological research. II. Regression analysis. Int J Epidemiol 2007;36:195-202 [PDF]
* Western B. Bayesian Analysis for Sociologists: An Introduction. Sociological Methods & Research 1999;28:7-34 [PDF]
* Gurrin LC, Kurinczuk JJ, Burton PR. Bayesian statistics in medical research: an intuitive alternative to conventional data analysis. J Eval Clin Pract 2000;6:193-204 [PDF]
Feldman HA, Proschan MA, Murray DM, Goff DC, Stylianou M, Dulberg E, McGovern PG, Chan W, Mann NC, Bittner V. Statistical design of REACT (Rapid Early Action for Coronary Treatment), a multisite community trial with continual data collection. Control Clin Trials 1998;19:391-403. [PDF]
Hannan PJ Experimental social epidemiology: Controlled community trials." Pp. 335-364 in Methods in Social Epidemiology, edited by J. Michael Oakes and Jay S. Kaufman, 2006. San Francisco: Jossey-Bass / Wiley. [PDF]
Fisher LD. Advances in clinical trials in the twentieth century. Annu Rev Public Health 1999;20:109-24. [PDF]
DeMets DL. Statistical issues in interpreting clinical trials. J Intern Med 2004;255:529-37. [PDF]
* Kaufman JS, Kaufman S, Poole C. Causal inference from randomized trials in social epidemiology. Soc Sci Med 2003;57:2397-409. [PDF]
Knol MJ, Vandenbroucke JP, Scott P, Egger M. What do case-control studies estimate? Survey of methods and assumptions in case-control research. Am J Epidemiol 2008;168:1073-81. [PDF]
Barlow WE, Ichikawa L, Rosner D, Izumi S. Analysis of case-cohort designs. J Clin Epidemiol 1999;52:1165-72. [PDF]
Maclure M, Mittleman M. Should we use a case-crossover design? Annu Rev Public Health 2000;21:193-221. [PDF]
Diaz Roux AV. Multilevel analysis in public health research. Annu Rev Public Health 2000;21:171-92. [PDF]
Oakes JM. The (mis)estimation of neighborhood effects: causal inference for a practicable social epidemiology. Soc Sci Med 2004;58:1929-52. [PDF]
Wakefield J. Ecologic studies revisited. Annu Rev Public Health 2008;29:75-90 [PDF]
Greenland S. Ecologic versus individual-level sources of bias in ecologic estimates of contextual health effects. Int J Epidemiol 2001;30:1343-50 [PDF]