Chapter 6 1

Chapter 6

Experiments in the Real World

Chapter 6 2

Clinical Trials

Experiments that study the effectiveness of medical treatments on actual patients.

Chapter 6 3

Thought Question 1Suppose you are interested in determining if drinking a glass of red wine each day helps prevent heartburn. You recruit 40 adults age 50 and older to participate in an experiment. You want half of them to drink a glass of red wine each day and the other half to not do so. You ask them which they would prefer, and 20 say they would like to drink the red wine and the other 20 say they would not. You ask each of them to record how many cases of heartburn they have in the next six months. At the end of that time period, you compare the results reported from the two groups. Give three reasons why this is not a good experiment.

Chapter 6 4

Randomization in Expts.

Completely Randomized Design

The experimental units are divided into different groups through a process of random selection.

Chapter 6 5

Blocking

Refers to the idea of only making comparisons within relatively similar groups of subjects

In the smoking lung cancer example, we could “block” age, subjects in a block will have similar ages.

Completely Randomized Block Design

Chapter 6 6

Blocking and randomization in expts.

Block to ensure fair comparisons with respect

to factors known to be important

Randomize to try to obtain comparability with

respect to unknown factors

Randomization also allows the calculation of

how much the estimates made from the study

data are likely to be in error

Chapter 6 7

Blocking and randomization in expts.

Block to ensure fair comparisons with respect to factors known to be important.

“Block what you can andrandomize what you cannot.”

Chapter 6 8

“Blocking” vs “stratification”“Blocking” word used in describing an experimental design

“Stratification” used in describing a survey or observational study

Both refer to idea of only making comparisons within relatively similar groups of subjects

Chapter 6 9

Blinding:

– Preventing people involved in an experiment from knowing which experimental subjects have received which treatment

– One may be able to blind subjects themselves people administering the treatments people measuring the results

Double blind:Both the subjects and those administering the treatments have been blinded.

Chapter 6 10

Chapter 6 11

Hawthorne, Placebo, and Experimenter Effects

The problem:– people may respond differently when they

know they are part of an experiment. The solution:

– use placebos, control groups, and double-blind studies when possible.

Chapter 6 12

Hawthorne, Placebo, and Experimenter Effects :

Case Study I1920’s Experiment by Hawthorne Works

of the Western Electric Company What changes in working conditions

improve productivity of workers?– More lighting?– Less lighting?– Other changes?

All changes improved productivity!

Chapter 6 13

Hawthorne, Placebo, and Experimenter Effects :

Case Study IIExperimenter Effects in Behavioral Research

(Rosenthal, 1976, Irvington Pub., p. 410) Teachers given a list of student names

– told these were students “who would show unusual academic development.”

IQ was measured at end of year– first graders on list: 15 points higher– second graders on list: 9.5 points higher– older: no striking difference

Great expectations = self-fulfilling prophecy– students were randomly selected (did not have high IQ)

Chapter 6 14

Experiments: Some Techniques

Matched Pairs

– to reduce a source of variability in responses

– the same or similar subjects receive each treatment

Chapter 6 15

(not) Double-Blinded: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

Not double-blinded– Participants know their treatment group

Single-blinded– Those measuring the IQ

Chapter 6 16

Double-Blinded:Case Study

Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp. 595-600)

Variables:– Explanatory: Treatment assignment– Response: Cessation of smoking (yes/no)

Double-blinded– Participants do not know which patch they

received– Nor do those measuring smoking behavior

Chapter 6 17

Experiments:Difficulties and Disasters

Extraneous variables– Confounding variables (in chapter 5)

– Interacting variables

Hawthorne, placebo, and experimenter effects

Refusals, non-adherers, dropouts Extending the results (generalizing)

Chapter 6 18

Interacting Variables The problem:

– effect of explanatory variable on response variable may vary over levels of other variables.

The solution:– measure and study potential interacting

variables. does the relationship between explanatory and

response variables change for different levels of these interacting variables?

if so, report results for different groups defined by the levels of the interacting variables.

Chapter 6 19

Interacting Variables:Case Study

Quitting Smoking with Nicotine Patches (JAMA, Feb. 23, 1994, pp. 595-600)

Researchers considered:– smoker at home

found this to be an interacting variable:

Percent quitting Nicotine Placebo

Smoker at home 31% 20%

No smoker at home 58% 20%

– other variables: age, weight, depression no interactions found

Chapter 6 20

Extending the Results( Can We Generalize? )

The problem:– lack of generalizability due to:

unrealistic treatments unnatural settings sample that is not representative of population

The solution:– Researchers should use natural settings

with a properly chosen sample.

Chapter 6 21

Extending the Results :Case Study

Does Aspirin Prevent Heart Attacks? (NEJM, Jan. 28, 1988, pp. 262-264)

Participants were measured in their natural setting (at home)

Only healthy male physicians were participants– Results may not apply to:

male physical labourers women

Chapter 6 22

Example: # 6.16 Page111

The progress of a type of cancer differs in men and

women. A clinical experiment to compare four

therapies for this cancer therefore treats sex as a

blocking variable.

(a) You have 500 male and 300 female patients who

are willing to serve as subjects. Use a diagram to

outline a block design for this experiment.

Chapter 6 23

Example Cont.

(b) What are the advantages of a block design over a

completely randomized design using these 800 subjects?A block design allows the researchers to control for differences between

men and women. If, for example, the treatment is effective for men but not

women (or vice versa), the treatment might be found to be ineffective

overall if both genders are mixed together.

Chapter 6 24

Key Concepts

Double-Blind Experiment Difficulties and Disasters Experimental Designs

– Completely Randomized Design– Matched Pairs Design– Block Design

Chapter 6 25

Quiz In what sense does random allocation make

for comparisons that are fair or unbiased? What is a completely randomized design? What is blocking? Why do we use blocking in designing

experiments? What is a control group and why are control

groups used? What is a placebo effect?