1. Chapter 51 Experiments, Good and Bad

2. Chapter 52 Experimentation u An experiment is the process of subjecting experimental units to treatments and observing their response. u Only properly designed and executed experiments can reliably demonstrate causation.

3. Chapter 53 Common Language u Response variable –what is measured as the outcome or result of a study u Explanatory variable –what we think explains or causes changes in the response variable –often determines how subjects are split into groups u Subjects –the individuals that are participating in a study u Treatments –specific experimental conditions (related to the explanatory variable) applied to the subjects

4. Chapter 54 Thought Question 1 In studies to determine the relationship between two conditions (activities, traits, etc.), one of them is often defined as the explanatory (independent) variable and the other as the outcome or response (dependent) variable. In an experiment to determine whether the drug memantine improves cognition of patients with moderate to severe Alzheimer’s disease, whether or not the patient received memantine is one variable, and cognitive score is the other. Which is the explanatory variable and which is the response variable?

5. Chapter 55 Confounding (Lurking) Variables u The problem: –in addition to the explanatory variable of interest, there may be other variables that make the groups being studied different from each other –the impact of these variables cannot be separated from the impact of the explanatory variable on the response

6. Chapter 56 Confounding u The effects from two or more variables cannot be distinguished from each other. Example: Smoking and Lung Cancer - Suppose most smokers are adults - Is Cancer due to age or smoking

7. Chapter 57

8. 8 Confounding (Lurking) Variables u The solution: –Experiment: randomize experimental units to receive different treatments (possible confounding variables should “even out” across groups) –Observational Study: measure potential confounding variables and determine if they have an impact on the response (may then adjust for these variables in the statistical analysis)

9. Chapter 59 Randomization in Expts. u Randomized Comparative Experiments The experimental units are divided into different groups through a process of random selection.

10. Chapter 510 The Role of Randomization Well designed statistical studies employ randomization to avoid subjective and other biases. u Experiments should use random assignment of experimental subjects to treatment groups –to ensure comparisons are fair –i.e., treatment groups are as similar as possible in every way except for the treatment being used.

11. Chapter 511 Some Jargons u Control group: –group of experimental units that is given no treatment. –treatment effect is estimated by comparing each treatment group with the control group. u Placebo: An inert dummy treatment. u Placebo effect: Response caused in human subjects by the idea that they are being treated.

12. Chapter 512 Thought Question 2 In an observational study, researchers observe what individuals do (or have done) naturally, while in an experiment, they randomly assign the individuals to groups to receive one of several “treatments.” Give an example of a situation where an experiment would not be feasible and thus an observational study would be needed.

13. Chapter 513 Thought Question 3 In testing the effect of memantine on the cognition of Alzheimer’s disease patients (from TQ #1), how would you go about randomizing 100 patients to the two treatment groups (memantine group & placebo group)? Why is it necessary to randomly assign the subjects, rather than having the experimenter decide which patients should get which treatment?

14. Chapter 514 Randomized Experiment versus Observational Study Both typically have the goal of detecting a relationship between the explanatory and response variables. u Experiment –create differences in the explanatory variable and examine any resulting changes in the response variable u Observational Study –observe differences in the explanatory variable and notice any related differences in the response variable

15. Chapter 515 Why Not Always Use a Randomized Experiment? u Sometimes it is unethical or impossible to assign people to receive a specific treatment. –-Smoking/Lung cancer Experiment. u Certain explanatory variables, such as handedness or gender, are inherent traits and cannot be randomly assigned.

16. Chapter 516 Control Group: Case Study Mozart, Relaxation and Performance on Spatial Tasks (Nature, Oct. 14, 1993, p. 611) u Variables: –Explanatory: Relaxation condition assignment –Response: Stanford-Binet IQ measure u Active treatment: Listening to Mozart u Control groups: –Listening to relaxation tape to lower blood pressure –Silence

17. Chapter 517 Statistical Significance u If an experiment or observational study finds a difference in two (or more) groups, is this difference really important? u If the observed difference is larger than what would be expected just by chance, then it is labeled statistically significant. u Rather than relying solely on the label of statistical significance, also look at the actual results to determine if they are practically important.

18. Chapter 518 Example: # 4.20 Pages 91-92 A large study used records from Canada’s national health care system to compare effectiveness of two ways to treat prostrate disease. The two treatments are traditional surgery and a new method that does not require surgery. The records described many patients whose doctors had chosen the other method. The study found that patients treated by the new method were significantly more likely to die within 8 years. (a) Further study of the data showed that this conclusion was wrong. The extra death among patients treated with the new method could be explained by lurking variables. What lurking variables might be confounded with a doctor’s choice of surgical or nonsurgical treatment?

19. Chapter 519 Example Cont. Patients who have little chances of survival would probably be referred to the new treatment – no need going through painful surgery, save money and hospital admission. (b) You have 300 prostrate patients who are willing to serve as subjects in an experiment to compare the two methods. Use a diagram to outline the design of a randomized comparative experiment.

20. Chapter 520 Key Concepts u Critical evaluation of an experiment or observational study u Common terms –explanatory vs. response variables –treatments, randomization u Randomized experiments –basic principles and terminology –problem with confounding variables