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Chapter 6. STA 200 Summer I 2011. Equal Treatment of All Subjects. The underlying assumption of randomized comparative experiments is that all subjects are handled equally in all respects except for the treatments being compared.
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Chapter 6 STA 200 Summer I 2011
Equal Treatment of All Subjects • The underlying assumption of randomized comparative experiments is that all subjects are handled equally in all respects except for the treatments being compared. • If the subjects aren’t handled equally in other respects, there might be bias.
Knowledge of Placebos • If a patient knows that they are receiving a placebo, we won’t be able to gauge the extent of the placebo effect. • If a doctor knows that a patient is receiving a placebo, the doctor may treat the patient differently.
Double-Blind Experiments • A double-blind experiment is one in which: • The standard for experiments is a “randomized, double-blind, placebo-controlled trial.”
Example • A researcher told 13 people who were sensitive to poison ivy that the stuff being rubbed on one of their arms was poison ivy. It was really a placebo, but all 13 broke out in a rash. • The stuff rubbed on their opposite arms was really poison ivy, but they were told it was a placebo. 2 of the 13 people broke out in a rash.
Problems with Experiments • Refusals • individuals who refuse to participate • problem for experiments dealing with major diseases • Nonadherers • don’t follow their assigned treatment • may not take treatment as prescribed, or take additional treatments on their own • Dropouts • begin the experiment, but don’t complete it • bias occurs if dropouts happen due to a reaction to one of the treatments
Generalizing Experimental Results • In order to generalize results from a group of experimental subjects to the population of interest: • The results must be statistically significant. • The environment of the experiment should be realistic. • We can only generalize for the population considered in the study.
Completely Randomized Design • The basic kind of experimental design is a completely randomized design, where the subjects are randomly allocated among all the treatments.
More Elaborate Experimental Designs • Multiple explanatory variables: • You can have them if you want. • Matched Pairs Design: • useful for comparing two treatments • Block Design: • useful for comparing subgroups
Matched Pairs Design • Two treatments are compared • There are two possible designs:
Matched Pairs Design Example An experiment to determine if hypnosis affects learning: • Each subject learns two lists of 16 word-number pairs (one awake, one hypnotized). The lists are similar in difficulty, and the order is randomized. • After listening several times, the subject repeats the list. The response variable is the number of errors.
Another Matched Pairs Example • In order to determine if using a new instructional software in the classroom improves test scores in middle schools, we first find two similar schools. • We then randomly assign the software to one of the schools. The other school continues with their current routine.
Block Design • like stratified random sampling for experiments • A block of subjects is a group known to be similar in some way that is expected to affect the response to the treatments. • First, the group of subjects is broken up into blocks. Treatments are then assigned randomly within each block.
Block Design Example An experiment comparing a low-fat and low-carbohydrate diet on weight loss: • Researchers are concerned that the effect of diet may depend on gender, so gender is treated as a blocking variable. • There are 122 severely obese subjects: 52 men and 70 women.
