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Political Science
Todd Alway

Political Science 3N06 2013 Lecture 5b: Experimental methods If you want to increase your internal validity and be confident, how do you rule out all of the other variables like maturation, how can you improve your research design? Introduce a control group: you have to make sure your control group is exactly the same as the experimental group except that the control group isn’t introduced to the independent variable. Having an equivalent control group is a way to eliminate all other variables and a way to improve your internal validity. The groups have to be treated equally - Some of the limitations of a one group pretest/post-test design can be countered by using a control group o A group that should resemble the experimental group in every aspect but one – it is not exposed to the independent variable - Scores between the control group and the experimental group can be compared – with the difference being attributed to the independent variable - Using a control group can increase the internal validity of an experiment - Threats to the internal validity of an experiment continued: - 9. Selection Bias - Control groups only form a control when they are effectively equivalent to the experimental group - “Selection bias” (in this context) implies that the control and experimental group are not equivalent - If so, then the difference in scores in the post-test (between groups) may be reflecting the difference in subjects, not the effect of the independent variable that we are interested in - Ways to enhance pre-test group equivalence - A) Probability sampling - We will discuss probability sampling next lecture - B) Random assignment - Researchers rely on volunteers not on probability sampling - You take the group that volunteers, and you randomly divide them into two groups; control and experimental. You have to use a random method to decide who goes into which group. 1 - Individuals in the sample are assigned to the control or the experimental group on the basis of random chance alone - As long as the groups are of a sufficient size, random assignment should equalize their average characteristics - Using chance and chance alone are more likely to equalize the characteristics of each group. - Sufficiently large groups- atleast 30 subjects each makes the chance of both groups being equivalent better - The bigger your sample the less likely you’ll have a mismatch in terms of the variables you need equal - C) Matching - Where groups are small, random assignment may not work to equalize the experimental and control groups - In that case, matching individuals into pairs (on the basis of shared characteristics) o And then splitting the pairs – with one member going into the control and one into the experimental group o May be the more appropriate option - Although even here – which characteristics should be relevant for the matching process? - Can you find subjects that are perfectly matched on all relevant variables? - Limitation: how do you know what to match on? You don’t know which variables are affecting your IV. - It is also really hard to split a group in
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