對撞因子不會直接造成影響它的變數之間出現相關,以路徑分析(英语:path analysis)或環路圖的術語來說,對撞因子會「阻斷」兩個變數間的路徑。然而,想要了解變數間的因果關係時,對撞因子非常重要,因為在設計實驗、挑選樣本或統計分析時,如果有意或無意間控制了對撞因子,會造成自變數(X)和應變數(Y)之間出現沒有實際因果關係的偽關係,稱為選擇偏誤(英语:selection bias)或伯克森悖論(英语:Berkson's paradox),如果控制對撞因子後造成相反的相關性,稱為辛普森悖論。用環路圖的術語來說,控制對撞因子會「開啟」 X 和 Y 之間的路徑,而造成偏誤。[3][4][5]
^Hernan, Miguel A; Robins, James M, Causal inference, Chapman & Hall/CRC monographs on statistics & applied probability, CRC: 70, 2010, ISBN 978-1-4200-7616-5
^Greenland, Sander; Pearl, Judea; Robins, James M, Causal Diagrams for Epidemiologic Research (PDF), Epidemiology, January 1999, 10 (1): 37–48 [2019-05-22], ISSN 1044-3983, OCLC 484244020, PMID 9888278, doi:10.1097/00001648-199901000-00008, (原始内容 (PDF)于2016-03-03)
^Pearl, Judea. Fusion, Propagation and Structuring in Belief Networks. Artificial Intelligence. 1986, 29 (3): 241–288. doi:10.1016/0004-3702(86)90072-x.
^Pearl, Judea. Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann. 1988.
^ 6.06.1Pearl, Judea; Dana Mackenzie. The Book of Why: The New Science of Cause and Effect. 2018: 111-114. ISBN 9780465097609.
^Mangel, M. and Samaniego, F. Abraham Wald’s work on aircraft survivability. Journal ofthe American Statistical Association. 1984, 79: 259–267.
^Asendorpf JB, Rindermann H, Woodley MA, Stratford J, Rabaglia C, Marcus G, Lane S. Bias due to controlling a collider: A potentially important issue for personality research (PDF). European Journal of Personality. 2012, 26: 391-413 [2020-02-03]. (原始内容 (PDF)于2017-07-25).