Threats to Validity from Confounding and Effect Modification • Overview: Random vs. systematic error • Confounding • Effect Modification • Logistic regression (time permitting) • Special thanks for some of the materials in these lecture: – Professor Jen Ahern (UCB) – Professor Madhu Pai (McGilll—a former 250b GSI) 1 Page 1
1 The cardinal rule of epidemiology • Remember that all results based on epidemiology studies are likely to be … Page 2
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Example: Confounding •A colleague with outside funding believes that cigarette smoke is not a “cause” (in any sense) of lung cancer but that exposure to matches (yes, matches) is the cause.This colleague has conducted a large case control study to test the null hypothesis: Ho: “Matches are notassociated with lung cancer”.•What’s the rationale (in the Popperian sense) for stating the null hypothesis rather than the alternative:HA: “Matches areassociated with lung cancer”.•What does the colleague hope to do (in terms of hypothesis testing)•What do you think of the term “associated” –would it be better to write “a cause of”? Page 4
• “We can never finally prove our scientific theories, we can merely (provisionally) confirm or (conclusively) refute them.” – - Karl Popper Sir Karl Raimund Popper CH FBA FRS  (28 July 1902 – 17 September 1994) was an Austrian-British  philosopher and professor at the London School of Economics .  He is generally regarded o regarded as one of the greatest philosophers of science of the 20th century.  Popper is known for his rejection of the classical inductivist views on the scientific method , in favour of empirical falsification : regarded as one of the greatest philosophers of science of the 20th century.  (wikipedia.com) Page 5
Confounding: smoking, matches,and lung cancer•Your colleague has located 1000 cases of lung cancer, of whom 820 carry matches.•Among 1000 reference patients (selected randomly from a population with recently taken normal chest x-rays), 340 carry matches.•Strengths of the reference selection process?Weaknesses?•Describe the relationship between matches and lung cancer in your colleague’s data.•Would you like to analyze the data in any other fashion? 10 Page 6
Confounding: smoking, matches, and lung cancer • You decide to look at the relationship between matches and lung cancer in the smokers separately from the non- smokers. • You find that among the 1000 cases, 900 are smokers and 810 (of the 900) carry matches • Among the 1000 reference patients, 300 are smokers and 270 (of the 300) carry matches • Calculate the relevant measure(s) of effect.
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- Fall '19
- Epidemiology, Confounding, Case-control study, Statistical terminology