SCOPE 2014 THE INTERDISCIPLINARY VOCATION OF POLITICAL SCIENCE(S)
Political Science Scope and Methods Introduction to Research Design and The Experimental Method.
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Transcript of Political Science Scope and Methods Introduction to Research Design and The Experimental Method.
Political Science Scopeand Methods
Introduction to Research Design and The Experimental Method
Introduction to Research Design
Scientific method (again) Theory development
What qualifies as a theory? Van Evera’s view
Theory testing Van Evera: Positivist approach
Inductive vs. deductive theorizing
Some Terminology
Dependent Variables (DV) and Independent Variables (IV) Van Evera definition Alternative conception:
We explain particular phenomenon – our DV – as a function of specific explanations – our IVs.
Examples Strategies
Terminology (continued)
Internal vs. External validity Internal validity: the “real effect.” External validity: “generalizability.” Threats to validity
Example (internal): School vouchers Example (external): Social psychology
Bottom Line (76 pages of Campbell and Stanley later): Be Careful!
Testing theories
Van Evera: 2 ways to test theories: Experimentation Observation
Case studies “Large N” (statistical) analysis
Experiments
Experimentation: Lab experiments
Effect of negative advertisements (Ansolabehere) Study of political cognition (Berinsky)
Field experiments Effect of canvassing, telephone calls, and mailing on
turnout (Green and Gerber) Effectiveness of “franking” – baby books and ballots
(Cover and Brumberg) Survey Experiments
War in Iraq (Berinsky)
Example: Iraq War
Please give your best guess to this next question, even if you are not sure of the correct answer. As you know, the United States is currently involved in a war in Iraq. Do you happen to know how many soldiers of the U.S. military have been killed in Iraq since the fighting began in March 2003?
Log (Base 10) of Estimates of U.S. Troop Deaths in Iraq, 2004
0.1
.2.3
.4.5
Fra
ctio
n
0 1 2 3 4 5Log(10) Casualties
Table 3:Predicted Probability of Causality
Estimates
Pr (Underestim
ate)
Pr (Correct Answer)
Pr (Overestima
te)Information
Low Information 0.51 0.31 0.18
High Information 0.36 0.56 0.07
Difference -0.15 +0.25 -0.11
Follow News About Iraq?
Not At All Closely 0.66 0.24 0.11
Very Closely 0.25 0.67 0.08
Difference -0.41 +0.43 -0.03
Partisanship
Strong Republican 0.48 0.44 0.08
Strong Democrat 0.35 0.54 0.12
Difference -0.13 +0.10 +0.04
Effect of Information Treatment on Support for War in IraqAmong Under-EstimatorsDid The U.S. Make The Right Decision in Using Military Force against Iraq?
Estimate War Deaths
Corrected Information
Right Decision 48% 44%
Wrong Decision 52% 56%
N=252; 2(1)=0.40 Pr=0.53Has The Current War in Iraq Been Worth Fighting?
Estimate War Deaths
Corrected Information
Worth Fighting 58% 53%
Not Worth Fighting
42% 47%
N=253; 2(1)=0.71 Pr=0.40
Among Over-estimatorsDid The U.S. Make The Right Decision in Using Military Force against Iraq?
Estimate War Deaths
Corrected Information
Right Decision 42% 42%
Wrong Decision 58% 58%
N=57; 2(1)=0.00 Pr=0.95Has The Current War in Iraq Been Worth Fighting?
Estimate War Deaths
Corrected Information
Worth Fighting 42% 48%
Not Worth Fighting
58% 52%N=572(1)=0.26 Pr=0.61
The Practice of Experimentation
Campbell and Stanley: The hard sellLimitation of experiments
Experimental work as the plutonic ideal
Experiments are about control Payoff in causal inference Maximize internal validity (if do them correctly) Random AssignmentRandom Assignment
Note: Random assignment random selection
Other Concerns
Construct validity Why does the treatment work? Is the treatment what we say it is?
Experiments vs. Quasi Experiments
Experiments: C&S – p.8: If you use random assignment, you don’t need to worry about internal validity
Quasi-Experiments: C&S – p. 40,56 – things are not so neat Specific threats to worry about Designs that control for all threats to validity
might be hard to operationalize
Example
Enid wants to investigate the effect of saliency of message on attitude change. From an old Ph.D. she finds a swell communication on the importance of physical sciences in a liberal education. Fortunately for her, Widget University conducts separately - English classes for engineers and liberal arts majors. Within this limitation, however, the university has matched the classes carefully on age, sex composition, socioeconomic background, and College Entrance Board Scores (both verbal and mathematical ability as well as on scores in specific subjects). Enid checks on the dean's records and is happy to find that the classes have indeed been matched to the best possible extent. Enid then delivers the message to the engineers (the salient group) and to the liberal arts students (the non-salient group). The engineers show much more attitude change. Enid concludes that message saliency increases attitude change.