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Lecture 6

POL222H1 Lecture 6: Types of Experiments

4 Pages

Political Science
Course Code
Kenichi Ariga

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POL222 Lecture 6 – Experiments Part 2 • Controlled Randomized Experiment o Is a research design which the researcher controls the value of the independent variable o The researcher must manipulate the value ▪ Addresses the concerns of reverse causality and simultaneity o The researcher randomly assigns values of the independent variable to the participants ▪ Addresses the concerns of confounding variable • E.g., (Random Assignment) Participants  Control Group  Y. X=0 • Participants  Treatment group Y. X=1 • By assignment each individual to different group, we would have same people and characteristics in a different group so it’s balanced • After diving them into the group, we will observe the outcome for each group • Even when we randomly assign the participants in a different group, we might invite another in the group unless experiment stimulus in each group o We give a new drug to the treatment group, and a fake drug to the control group o Unless we do this, we cannot really find the causal impact in the new drug • In order to single out the impact of negative message, we have to show something similar to the control group that might have a neutral or positive message • Without new content we cannot single out a single impact for the bias • We have a complete control over that makes a clear order over X and Y • All the confounding variables observed or not have to be balanced between treatment or controlled • Experimental stimulus  should be careful how we control experimental stimulation • Different Types of Experiments • Lab Experiments o Conducted in a lab setting o Recruit voluntary participants • Field Experiments o Conducted in a real-world setting o Become more popular today • Survey Experiments o A sample of people randomly selected from a large population ▪ E.g., population  random sample  through [random assignment] to control group or  treatment group o Most basic is population of people in sample are equal o We can learn the characteristics of relationship in population and in the sample o Random sample will provide you representative sample  tell you the relationship in the population o Random sample helps you choose from population o Random assignment is a procedure which you will divide when you try to identify causal relationship • Survey Experiments for Causal Inference • Question: Does conscription reduce the public support for war? o Contradictory Theoretical Arguments: ▪ Conscription would reduce support for war, as larger segment of population must bear a direct cost of the war and perceive greater risk • Everyone may have someone fighting for war for themselves so they would be careful about the war • Many would oppose going to war ▪ Opposite: Conscription would increase support for war, as larger segment of population has a direct stake in the outcome, and causalities are born fairly • Importance for war and this increase support for war because many people would consider that the country is engaging • Conscription  Public Support for War • Nature of War (may also be a confounding variable)  Conscription • They needed to involve a large segment of the population thus it would affect how families support the war or if people are actually engaged • In an idea scenario, if you can randomly assign rather the country can use conscription or public support and how each country will feel about it …but that’s impossible o Because we cannot randomly assign to each country • A survey of approx. 2000 randomly-sampled individuals in the US o Randomly manipulate beliefs about the likelihood of conscription in near future ▪ Treatment: tell respondents a news story about members of Congress calling for reintroduction of military draft
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