1 Chapter 6 Causal Design © 2005 Thomson/South-Western.

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Presentation transcript:

1 Chapter 6 Causal Design © 2005 Thomson/South-Western

2 Types of Evidence That Supports a Causal Inference Concomitant variation--evidence of the extent to which X and Y occur together or vary together in the way predicted by the hypothesis Time order of occurrence of variables-- evidence that shows X occurs before Y Elimination of other possible causal factors—evidence that allows the elimination of factors other than X as the cause of Y X -- the presumed cause Y -- the presumed effect

3 Types of Experiments Scientific investigation in which an investigator manipulates and controls one or more independent variables and observes the dependent variable for variation concomitant to the manipulation of the independent variables Laboratory Experiment Experiment Field Experiment Research study in a realistic situation in which one or more independent variables are manipulated by the experimenter under as carefully controlled conditions as the situation will permit Research investigation in which investigator creates a situation with exact conditions so as to control some, and manipulate other, variables

4 Types of Extraneous Factors That Can Contaminate Research Results History --Specific events external to an experiment, but occurring at the same time, which may affect the criterion or response variable Maturation --Processes operating within the test units in an experiment as a function of the passage of time per se Testing --Contaminating effect in an experiment due to the fact that the process of experimentation itself affected the observed response  Main testing effect--the impact of a prior observation on a later observation  Interactive testing effect--the condition when a prior measurement affects the test unit’s response to the experimental variable

5 Types of Extraneous Factors That Can Contaminate Research Results Instrument Variation --Any and all changes in the measuring device used in an experiment that might account for differences in two or more measurements Statistical Regression --Tendency of extreme cases of a phenomenon to move toward a more central position during the course of an experiment Selection Bias --Contaminating influence in an experiment occurring when there is no way of certifying that groups of test units were equivalent at some prior time Experimental Mortality --Experimental condition in which test units are lost during the course of an experiment

6 Randomly sample 100 healthy people during flu season. Randomly Assign 50 get daily vitamin C tablets 50 get daily placebo tablets Days later: Count # colds in each group Figure 1a: Example of a Classic Scientific Experiment

7 Randomly sample 100 consumers. Randomly Assign 50 see package design “A” 50 see package design “B” Count # your brand purchased in ea group Figure 1b: Example of a Marketing Research Experiment

8 Figure 2: Some Possible Outcomes in a Time-Series Experiment when Introducing an Experimental Variable X O 1 O 2 O 3 O 4 X O 5 O 6 O 7 O 8 Time ABCDEABCDE

9 Figure 3: Some Popular Standard Test Markets Midland TX Oklahoma City, OK Tulsa OK Wichita KS Lexington/ Fayette KY Charleston WV Bloomington IN Indianapolis IN Springfield IL Rockford IL

10 Figure 4: A Perspective on Various Types of Test Markets Simulated Test Market Controlled Test Market stop Standard Test Market stop promising not promising National Rollout