Chapter 2 Notes Math 1680

Math 1680 Assignments Look over Chapter 1 and 2 before Wednesday Assignment #2: Chapter 2 Exercise Set A (all, but #7, 8, and 10) due on Monday, January 31 st. By Wednesday Jan 26th, do Ch 2 review exercises (not to turn in). Will discuss in class. Quiz 1 will be over the reading for Chapter 1 Don’t forget Prerequisite Verification is due to me by Friday Jan 28 th at 3pm. If you want a copy of these notes, me and I will reply with them attached.

Section 1 Controlled experiments vs. observational studies –In a control experiment, the investigators choose who is in the control group and who is in the treatment group –In an observational study the subject assign him or herself to the treatment or the control group, and the investigators solely observe what is going on. –Controlled experiment and observational study still have both a treatment group and a control group.

Examples of need for observational vs. controlled A study of the effects of smoking A study of the effects of sexual promiscuity A study of the effects of being an alcoholic –These are all things that someone is not going to take part in for 10 years without it being a regular habit, thus the need for observation study

Causation versus Association In an observational study of smokers and nonsmoker, there is more common occurrence of heart attacks, lung cancer, and many other diseases among smokers. –Thus there is a strong association between smokers and these diseases.

“Association is circumstantial evidence for causation. However, the proof is incomplete.” There could be confounding factors that are not being considered –(In the case of smoking, the idea of other confounding factors were found implausible and that if you quitting smoking, you will live longer.)

Ways to “control” confounding Investigate how a control is selected –Was the control group truly similar to the treatment group aside from the exposure of interest? Techniques when confounding factors are identified –Make comparisons in smaller more homogeneous groups

Examples in the study of smokers Confounding factor: gender –Men are more susceptible to heart disease than women –Thus, they compared male smokers to male nonsmokers Confounding factor: age –Thus, they compared male smokers age to male nonsmokers age 55-59

Section 2 The Coronary Drug project –Randomized, controlled double-blind –One drug tested: Clofibrate Death rate: 20% treatment group and 21% control group, thus Clofibrate does not save lives Suggested confounding factor: adherence See Table 1 on page 14

Conclusion Clofibrate does not have an effect Adherers are different from non-adherers –Remember: comparing adherers to non- adherers is an observation study because the patients made the decision to adhere or not.

Section 3 (More Examples) Pellagra –Sporadically hit villages –Sanitary conditions is diseased households was poor and had many flies –One such blood-sucking fly (Simulium) had the same geographic range as Pellagra –Did pellagra spread through insects?

Conclusion “Pellagra was caused by bad diet, and is not infectious” –Poorer villages had more restrictive diets –“The flies were a marker of poverty, not a cause of Pellagra” –Association does not imply causation Read through next three examples on your own…

Section 4 Sex Bias at the University of California, Berkeley Graduate Admissions –44% of male applicants admitted –35% of female applicants admitted –Is there discrimination taking place? What needs to be done? Look at more homogeneous groups….

College Admission Bias

Notice Over 50% of the men applied to the first two majors that were easier to get into Over 90% women applied to the later four that were much harder to get into Choice of major was a confounding factor Weighted averages show no discrimination

Simpson’s Paradox –Relationship between percentages in subgroups can be reverse when the subgroups are combined Read Section 5 on your own time…

Class Discussion Ch 2 review exercises and any other pertinent questions.