Chapter 5

1. Chapter 5 Experiments, Good and Bad Chapter 5

2. What are some terms we need to know? • Response variable • what is measured as the outcome or result of a study • Explanatory variable • what we think explains or causes changes in the response variable • often determines how subjects are split into groups • Subjects • the individuals that are participating in a study • Treatments • specific experimental conditions (related to the explanatory variable) applied to the subjects Chapter 5

3. Randomized Experiment versus Observational Study Both typically have the goal of detecting a relationship between the explanatory and response variables. • Experiment • create differences in the explanatory variable and examine any resulting changes in the response variable • Observational Study • observe differences in the explanatory variable and notice any related differences in the response variable Chapter 5

4. Randomization:Case Study • Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp. 595-600) • Variables: • Explanatory: Treatment assignment • Response: Cessation of smoking (yes/no) • Treatments • Nicotine patch • Control patch • Random assignment of treatments Chapter 5

5. Case Study • Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp. 595-600) • Variables: • Explanatory: Treatment assignment • Response: Cessation of smoking (yes/no) • Treatments • Nicotine patch • Control patch • Random assignment of treatments Chapter 5

6. Why Not Always Use a Randomized Experiment? • Sometimes it is unethical or impossible to assign people to receive a specific treatment. • Certain explanatory variables, such as handedness or gender, are inherent traits and cannot be randomly assigned. Chapter 5

7. Placebo:Case Study • Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp. 595-600) • Variables: • Explanatory: Treatment assignment • Response: Cessation of smoking (yes/no) • Treatments • Nicotine patch • Placebo: Control patch • Random assignment of treatments Chapter 5

8. Case Study • Meditation and Aging (Noetic Sciences Review, Summer 1993, p. 28) • Variables: • Explanatory: Observed meditation practice (yes/no) • Response: Level of age-related enzyme • Treatment not randomly assigned Chapter 5

9. Experiments: Basic Principles • Randomization • to balance out extraneous variables across treatments • Placebo • to control for the power of suggestion • Control group • to understand changes not related to the treatments Chapter 5

10. Control Group:Case Study • Mozart, Relaxation and Performance on Spatial Tasks (Nature, Oct. 14, 1993, p. 611) • Variables: • Explanatory: Relaxation condition assignment • Response: Stanford-Binet IQ measure • Active treatment: Listening to Mozart • Control groups: • Listening to relaxation tape to lower blood pressure • Silence Chapter 5

11. Confounding (Lurking) Variables • 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 Chapter 5

12. Confounding (Lurking) Variables • 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) Chapter 5

13. Confounding Variables:Case Study • Heart or Hypothalamus? (Scientific American, May 1973, pp. 26-29) • Infants were not randomized to either hear the heartbeat sound or not • Same nursery was used on subsequent days with different groups of babies • Environment variables • construction noise • temperature Chapter 5

14. Statistical Significance • If an experiment or observational study finds a difference in two (or more) groups, is this difference really important? • If the observed difference is larger than what would be expected just by chance, then it is labeled statistically significant. • Rather than relying solely on the label of statistical significance, also look at the actual results to determine if they are practically important. Chapter 5

15. Key Concepts • Critical evaluation of an experiment or observational study • Common terms • explanatory vs. response variables • treatments, randomization • Randomized experiments • basic principles and terminology • problem with confounding variables Chapter 5

16. Do Now 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? Chapter 5

17. 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. Chapter 5

18. 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? Chapter 5