Introduction: Research design 17.871 Spring 2012 1.
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Transcript of Introduction: Research design 17.871 Spring 2012 1.
Introduction: Research design
17.871
Spring 2012
1
The Biggest Problem in Research: Establishing Causality Return to the case of voting machine problems
in Florida After the election, we wanted to know: are some
machines “better” than others? For the policy choice, we want to know if
2
The Biggest Problem in Research: Establishing Causality Return to the case of voting machine problems
in Florida After the election, we wanted to know: are some
machines “better” than others? For the policy choice, we want to know if
3
The Biggest Problem in Research: Establishing Causality Return to the case of voting machine problems
in Florida After the election, we wanted to know: are some
machines “better” than others? For the policy choice, we want to know if
4
The Biggest Problem in Research: Establishing Causality Return to the case of voting machine problems
in Florida After the election, we wanted to know: are some
machines “better” than others? For the policy choice, we want to know if
5
The problem
How do we make sure that quality differences observed among machine types are due to machine types per seThis is an issue of causalityWe attend to “internal validity” so that when
we observe differences between groups, we can assure ourselves that this is because of the “treatments” of interest
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Review of internal and external validity
Internal validity: the two problemsThe two primary threats to internal validity.
1. Nonrandom selection into the treatment group (confounding variables) Comparing
apples with apples or apples with oranges?
Random assignment ensures apple to apple comparisons
Regression, matching, difference-in-differences also attempt to compare apples with apples
2. Reverse causation The chicken and egg problem, which came
first? Is your dependent variable influencing your
treatment (your explanatory variable)? If you can address these problems, you almost
always have an internally valid study Randomly assigned experiments address both
External validity
Is your sample representative of the population? Make sure your study population is relevant to the
general population Address by randomly sampling
Good research is about addressing Internal validity External validity
Clarification
Randomly sampling cases gets you? External validity
Randomly assigning to treatment group? Internal validity
Controlling for variables with regression addresses? Internal validity
What study design addresses both internal and external validity? Field experiments
What is gold standard research design? Field experiment, e.g., Connecticut voting
turnout Why? Addresses
Internal validity Nonrandom selection into the treatment Reverse causation
External validity What aspects of our lives are governed by gold standard
research? In this class, we mostly do observational studies,
But the key to a successful observational research is always keep in mind how one study differs from a field experiment
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Next class: STATA
Kohler & Kreuter, Data analysis (2nd edition)
Chapter 1 Skip section 1.3.19 (linear regression)
Chapter 3 Only read section 3.1
Chapter 5 Read section 5.1 but skip 5.1.3 and 5.1.4 Read section 5.2
Handout: “How to use the STATA infile and infix commands” (course website)
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If you want to play around with Stata Visit
http://ist.mit.edu/services/software/athena/numerical for basic info about accessing Stata in Athena
Look on pp. xxi-xxii of Kohler & Kreuter for info about download example data
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