{ Chapter 6.2 Part 2
Experimental Design Terms Terms: Response variable – measures outcome (dependent, y) Explanatory variable – attempts to explain response (independent, x) Experimental Units – individuals being studied Factor - is the explanatory variable – it’s what we test Treatment – specific experimental condition Level – amount or degree of treatment
Placebo - dummy treatment response to a placebo is call the placebo effect Control group (given placebo, no treatment, or accepted treatment – helps control lurking variables) Statistically significant – observed effect too large to attribute to chance
Principles of Experimental Design 1)Control – to counter effects of lurking variable(s) (simplest form is comparison) 2)Randomization – use impersonal chance to assign subjects to treatment. It is used to make the treatment groups as equal as possible and to spread the lurking variables throughout all groups 3)Replication – Repeat the experiment on many subjects to reduce the chance variation in the results.
Types of experiments 1) Blind – recipient does not know treatment 2) Double Blind – recipient and tester do not know treatment 3) Block Design – A block is a group of experimental units that are similar in ways that are expected to affect the response of the treatment (randomly assign within block) Justify reason for blocks! Blocking reduces variability within sample and offer control over lurking variables such as gender, age, etc 4) Matched pairs – Blocks are “alike” to better see result of treatment (twin studies) Can also compare before and after of same individual.
Matching the subjects in various ways can produce more precise results than simple randomization. Matched Pairs Design combines matching with randomization. It compares just two treatments. Choose subjects that are as closely matched as possible. Randomly assign the two treatments to the subjects in each pair. Matched Pairs
Pepsi wants to demonstrate the Coke drinkers prefer Pepsi when they taste both colas blind. The subjects, all people who said they were Coke drinkers, tasted both colas from classes without brand markings and said which they liked better. This is a matched pairs design in which each subject compares the two colas. Because responses may depend on which cola is tasted first, the order of tasting should be chosen at random for each subject. When more than half of the Coke drinkers chose Pepsi, Coke claimed that the experiment was biased. The Pepsi glasses were marked M and Coke glasses were marked Q. Aha, said Coke, the results would just mean that people like the letter M better than Q. The matched pair design is adequate, but a more careful experiment would avoid the distinction. Example:
Matching reduces the effects of variation among the subjects. We do not randomly assign all the subjects at once to the two treatments-we randomize only within each matched pair Matched pairs are an example of block designs
A block is a group of experimental subjects that are known before the experiment to be similar in some way that is expected to affect the response to the treatments. In a block design the random assignment of subjects to treatment is carried out separately within each block. Blocks are another form of control. They control the effects of some outside variable by bringing those variables into the experiment to form the blocks.
Women and men respond differently to advertising. An experiment to compare the effectiveness of three television commercials for the same product will want to look separately at the reactions of men and women, as well as assess the overall response to the ads. A completely randomized design considers all subjects, both male and female, as a single pool. The randomization assigns subjects to three treatment groups without regarding their sex. This ignores the difference between males and females. A better design considers women and men separately. Randomly assign women to one of the three groups, one to view each commercial. Then separately assign the men at random to the three groups. Example
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