Hivatkozások

Assmann, Susan F, Stuart J Pocock, Laura E Enos, és Linda E Kasten. 2000. „Subgroup analysis and other (mis)uses of baseline data in clinical trials”. The Lancet 355 (9209): 1064–9. https://doi.org/10.1016/S0140-6736(00)02039-0.

Button, Katherine S, John PA Ioannidis, Claire Mokrysz, Brian A Nosek, Jonathan Flint, Emma SJ Robinson, és Marcus R Munafò. 2013. „Power failure: why small sample size undermines the reliability of neuroscience”. Nature Reviews Neuroscience 14 (5): 365–76. https://doi.org/10.1038/nrn3475.

Dawid, A. P. 2000. „Causal Inference without Counterfactuals”. Journal of the American Statistical Association 95 (450): 407–24. https://doi.org/10.1080/01621459.2000.10474210.

Gachályi, Béla, Géza Lakner, és János Borvendég. 2003. Klinikai farmakológia a gyakorlatban. Springer Tudományos Kiadó.

Goodman, Steven N. 1999. „Toward Evidence-Based Medical Statistics. 1: The P Value Fallacy”. Annals of Internal Medicine 130 (12): 995–1004. https://doi.org/10.7326/0003-4819-130-12-199906150-00008.

Greenland, Sander, és James M Robins. 1986. „Identifiability, Exchangeability, and Epidemiological Confounding”. International Journal of Epidemiology 15 (3): 413–19. https://doi.org/10.1093/ije/15.3.413.

Greenland, Sander, Stephen J Senn, Kenneth J Rothman, John B Carlin, Charles Poole, Steven N Goodman, és Douglas G Altman. 2016. „Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations”. European journal of epidemiology 31 (4): 337–50. https://doi.org/10.1007/s10654-016-0149-3.

Lakner, Géza, Gábor Renczes, és János Antal. 2009. Klinikai vizsgálatok kézikönyve. SpringMed Kiadó.

Maldonado, George. 2013. „Toward a clearer understanding of causal concepts in epidemiology”. Annals of Epidemiology 23 (12): 743–49. https://doi.org/10.1016/j.annepidem.2013.09.001.

———. 2016. „The role of counterfactual theory in causal reasoning”. Annals of Epidemiology 26 (10): 681–82. https://doi.org/10.1016/j.annepidem.2016.08.017.

Maldonado, George, és Sander Greenland. 2002. „Estimating causal effects”. International Journal of Epidemiology 31 (2): 422–29. https://doi.org/10.1093/ije/31.2.422.

Price, Donald D., Damien G. Finniss, és Fabrizio Benedetti. 2008. „A Comprehensive Review of the Placebo Effect: Recent Advances and Current Thought”. Annual Review of Psychology 59 (1): 565–90. https://doi.org/10.1146/annurev.psych.59.113006.095941.

Schulz, Kenneth F, és David A Grimes. 2005. „Multiplicity in randomised trials I: endpoints and treatments”. The Lancet 365 (9470): 1591–5. https://doi.org/10.1016/S0140-6736(05)66461-6.

Senn, Stephen. 2003. Cross-over Trials in Clinical Research. Wiley.

———. 2013. „Seven myths of randomisation in clinical trials”. Statistics in Medicine 32 (9): 1439–50. https://doi.org/10.1002/sim.5713.

Sleight, Peter. 2000. „Debate: Subgroup analyses in clinical trials: fun to look at-but don’t believe them!” Trials 1 (1): 1–3. https://doi.org/10.1186/cvm-1-1-025.

Wartolowska, Karolina, Andrew Judge, Sally Hopewell, Gary S Collins, Benjamin J F Dean, Ines Rombach, David Brindley, Julian Savulescu, David J Beard, és Andrew J Carr. 2014. „Use of placebo controls in the evaluation of surgery: systematic review”. British Medical Journal 348. https://doi.org/10.1136/bmj.g3253.

Wasserstein, Ronald L., és Nicole A. Lazar. 2016. „The ASA Statement on p-Values: Context, Process, and Purpose”. The American Statistician 70 (2): 129–33. https://doi.org/10.1080/00031305.2016.1154108.

Yusuf, Salim, Janet Wittes, Jeffrey Probstfield, és Herman A. Tyroler. 1991. „Analysis and Interpretation of Treatment Effects in Subgroups of Patients in Randomized Clinical Trials”. JAMA 266 (1): 93–98. https://doi.org/10.1001/jama.1991.03470010097038.