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Warm-up. A newspaper article about an opinion poll says that “43% of Americans approve of the president’s overall job performance.” Toward the end of the article, you read : “The poll is based on telephone interviews with 1210 adults from around the United States, excluding Alaska and Hawaii.”
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Warm-up • A newspaper article about an opinion poll says that “43% of Americans approve of the president’s overall job performance.” Toward the end of the article, you read : “The poll is based on telephone interviews with 1210 adults from around the United States, excluding Alaska and Hawaii.” • What variable did this poll measure? • What population do you think the newspaper wants information about? • What was the sample? • Are there any sources of bias in the sampling method used?
Experiment vs. Observational Study • Recall: in an experiment, we actually do something to people, animals, or objects in order to observe the response. • Observational studies observe individuals and measure outcomes but do not impose treatment on the individuals.
Terminology • Experimental units: the individuals on which the experiment is conducted. • When units are people, we call them subjects or participants. • Treatment: the specific experimental condition applied to the units. • Example: a treatment might be 500 mg of naproxen, or 30 minutes of exercise per day…
Terminology • It is important to note the difference between response and explanatory variables in an experiment. • Factor – another name for explanatory variable • Level – a specific value of a factor (ex. dosage of medication) • Placebo – a “dummy” treatment
Example – Physician’s Health Study Beta Carotene Yes No • Does regularly taking aspirin or beta carotene help reduce the risk of a heart attack? • Subjects: 21,996 male physicians • Factors: Aspirin and Beta Carotene • Levels for each: Yes/No • Treatments: Four options Aspirin No Yes
Some ways to make experiments better • You need to have a control group. This is a group in which no treatment is given but all other aspects of the situation are the same. • The placebo effect… Some patients respond favorably even if they are not receiving treatment but think they are.
Comparative ExperimentsExample of Single Treatment Units Treatments Observe/Measure Response Single treatment designs are not optimal. There is no control group, and the design doesn’t control for placebo effect (when patients expect relief or improvement).
Comparative ExperimentsUsing a control group Group 1 Treatment 1 Compare Response Units Group 2 Treatment 2: Placebo The answer is RANDOMIZATION. You MUST label this if using a diagram and make a statement as to how you are going to randomize! The question is HOW DO WE DECIDE WHICH UNITS RECEIVE WHICH TREATMENT???
Principles of Experimental Design – Things you should consider and discuss in your answers. • Control – comparison of several treatments in to a group without treatment is the simplest form. • Randomization – randomly assign subjects to treatment groups in order to reduce systematic differences among the groups. • Replication – Replicate each treatment on many subjects to reduce chance variation in the results. You are more likely to find statistical significance if you have more people.
Illustration of Completely Randomized Design Choosing an adequately large sample ensures REPLICATION. Group 1 Treatment 1 Compare Response Random Assignment Group 2 Treatment 2: Placebo Random Assignment illustrates the principle of RANDOMIZATION. Having a control group illustrates the principle of CONTROL.
Caution • There is a difference between random selection of participants and random assignment of subjects to treatment groups. • Choosing an SRS is random selection. All of these participants are in the experiment. • Then, randomly assign those subjects to treatment groups.
Example 2 • A pharmaceutical engineer is studying the effects of a new medicine for pain relief. She wants to try two different dosages (500 mg and 1000 mg) and 3 different daily intakes (1/day; 2/day; and 3/day). Five people will be tested at each combination of dosage and daily intake. • Identify all the explanatory variables. • How many subjects are needed? • Outline in diagram form an appropriate design for this experiment. Indicate how many people are assigned to each treatment group • Use Table B starting at line 108 to select the people assigned to the 1st treatment group. How did you label the people?
Cautions about Experimentation • We need to treat all the experimental units in the exact same way except for the difference in treatment. • One way to accomplish this is by using a “double-blind” experiment. • Neither the subjects nor the personnel who have contact with them (especially the ones collecting the data) are aware of which treatment each subject receives.
Other Weaknesses in Experimental Designs • Lack of realism is a serious potential weakness. • In 1986, before a third brake light was required on cars, an experiment found that adding the third brake light to cars would reduce rear-end collisions by 50% • In actuality, the reduction was only 5%. What happened???
Another Favorite of the AP Gang – Matched Pairs • Gives individuals both treatments – very favorable because you can see differences for each person. • Example: You want to know what type of music makes students perform better on tests. You could give each student the same test twice but with different music each time. The order of test would be random.
Block Designs • Grouping by another factor first. • Example: You might “block” a cancer treatment study into gender. • Block designs can have blocks of any size (ex. 20 females and 50 males in the experiment). • In a block design, the random assignment of units to treatments is carried out separately within each block.
General Format of a Blocked Design Random Assignment Treatment 1 Observe/Compare Response Variable Block 1 Treatment 2 Treatment 3 Subjects Random Assignment Treatment 1 Observe/Compare Response Variable Block 2 Treatment 2 Treatment 3 Putting subjects into blocks is NOT random.
2002 #2 • A manufacturer of boots plans to conduct an experiment to compare a new method of waterproofing to the current method. The appearance of the boots is not changed by either method. The company recruits 100 volunteers in Seattle, where it rains frequently, to wear the boots as they normally would for 6 months. At the end of the 6 months, the boots will be returned to the company to be evaluated for water damage. • A) Describe a design for this experiment that uses the 100 volunteers. Include a few sentences on how it would be implemented. • B) Could your experiment be double-blind? Explain.
Homework Chapter 4 # 46, 50, 54, 56, 62