Araştırmalarda BİAS Nedenleri ve Araştırma Hataları
Synopsis
Bilimsel araştırmalarda tahminlerin doğruluğunu bozan sistematik hatalar ve taraf tutmalar (bias), çalışmanın iç ve dış geçerliliğini doğrudan etkileyen kritik unsurlardır. Bu hatalar temel olarak denek seçiminden kaynaklanan seleksiyon biası, veri toplama sürecindeki yanlışlıklardan doğan enformasyon biası ve etken ile sonuç arasındaki ilişkiyi bulandıran kafa karıştırıcı faktörler olmak üzere üç ana kategoride incelenmektedir. Yanıt vermeme, takip kaybı, hatalı öz raporlama ve hatırlama güçlüğü gibi faktörler sonuçların geçerliliğine gölge düşürse de, uygun çalışma tasarımı ve istatistiksel yöntemlerle bu yanlılıkların minimize edilmesi bilimsel ilerleme için esastır.
Systematic errors and biases in scientific research significantly undermine the accuracy of estimates and threaten both the internal and external validity of a study. These errors are primarily categorized into selection bias arising from participant recruitment, information bias stemming from measurement inaccuracies, and confounding factors that distort the causal link between exposure and outcome. While factors such as non-response, loss to follow-up, and recall inaccuracies compromise research integrity, minimizing these biases through rigorous design and analytical methods is essential for reliable scientific progress.
References
Dohoo IR. Bias--is it a problem, and what should we do? Prev Vet Med. 2014;113(3):331-7.
Tripepi G, Jager KJ, Dekker FW, Zoccali C. Selection bias and information bias in clinical research. Nephron Clin Pract. 2010;115(2):c94-9.
Alvarez RM, VanBeselaere C. Web-Based Survey. In: Kempf-Leonard K, editor. Encyclopedia of Social Measurement. New York: Elsevier; 2005. p. 955-62.
Hernan MA, Hernandez-Diaz S, Robins JM. A structural approach to selection bias. Epidemiology. 2004;15(5):615-25.
Babbie ER. Survey research methods. Belmont, Calif.: Wadsworth Pub. Co.; 1973.
Altman DG. Statistics in medical journals: some recent trends. Stat Med. 2000;19(23):3275-89.
Kristman V, Manno M, Cote P. Loss to follow-up in cohort studies: how much is too much? Eur J Epidemiol. 2004;19(8):751-60.
Siddiqui O, Flay BR, Hu FB. Factors affecting attrition in a longitudinal smoking prevention study. Prev Med. 1996;25(5):554-60.
Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychol Methods. 2002;7(2):147-77.
Bisgard KM, Folsom AR, Hong CP, Sellers TA. Mortality and cancer rates in nonrespondents to a prospective study of older women: 5-year follow-up. Am J Epidemiol. 1994;139(10):990-1000.
Westreich D. Berkson's bias, selection bias, and missing data. Epidemiology. 2012;23(1):159-64.
Hennekens CHBJEMSL. Epidemiology in medicine. Boston, Massachusetts: Little, Brown; 1987.
Althubaiti A. Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016;9:211-7.
Zhu K, McKnight B, Stergachis A, Daling JR, Levine RS. Comparison of self-report data and medical records data: results from a case-control study on prostate cancer. Int J Epidemiol. 1999;28(3):409-17.
Harrison L, Hughes A. Introduction--the validity of self-reported drug use: improving the accuracy of survey estimates. NIDA Res Monogr. 1997;167:1-16.
Holmberg L, Ohlander EM, Byers T, Zack M, Wolk A, Bruce A, et al. A search for recall bias in a case-control study of diet and breast cancer. Int J Epidemiol. 1996;25(2):235-44.
Weinstock MA, Colditz GA, Willett WC, Stampfer MJ, Rosner B, Speizer FE. Recall (report) bias and reliability in the retrospective assessment of melanoma risk. Am J Epidemiol. 1991;133(3):240-5.
Carroll RJ. Measurement Error in Epidemiologic Studies. Encyclopedia of Biostatistics2005.
Berner ES, Graber ML. Overconfidence as a cause of diagnostic error in medicine. Am J Med. 2008;121(5 Suppl):S2-23.
Grimes DA, Schulz KF. Bias and causal associations in observational research. Lancet. 2002;359(9302):248-52.
Jager KJ, Zoccali C, Macleod A, Dekker FW. Confounding: what it is and how to deal with it. Kidney Int. 2008;73(3):256-60.
