Final Exam Flashcards

(38 cards)

1
Q

Participant Observant

A

a method of qualitative research by which the researcher ob-
serves and engages with the community or social groups from which she wants to under-
stand a social phenomenon

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2
Q

Belmont Report

A

code providing guidelines for ethical research

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3
Q

3 Principles of the Belmont Report

A
  1. respect (for persons) 2. Benefit 3. Justice
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4
Q

Natural Experiment

A

researcher does not randomly
assign the level of the independent variable

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5
Q

4 Hurdles to establishing a casual relationship

A
  1. Is there a correlation between X and y?
  2. Can we rule out reverse causation?
  3. Is there a credible causal mechanism?
  4. Have we controlled for all confounding variables?
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6
Q

Goal of sampling

A

to make inferences about a
population by studying a sample

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7
Q

representative surveys

A

(we make informed estimates of how close we are to the true
population value)

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8
Q

target population

A

Population to which you would like to generalize your results

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9
Q

sampling frame

A

Set of all cases from which you will select the sample.

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10
Q

non-response bias

A

a bias that occurs when a certain group of people are the ones that respond to a survey

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11
Q

coverage
errors

A

failure to cover adequately all components of the population being studied

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12
Q

Survey Experiments

A

treatment is usually textual or information, DV is something
you could ask in a survey. Often online.

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13
Q

Lab Experiments

A

takes place in a lab. Often involves behavior, interaction or
fancy measurements (e.g., skin conductance)

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14
Q

Field Experiments

A

DV is usually real-world behavior, treatments vary.

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15
Q

Natural experiments

A

treatment is not assigned by researchers

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16
Q

Fundamental problem of causal inference

A

for any individual unit, we can observe only one of Y(1) or Y(0) (controlled by limiting confounders)

17
Q

Internal validity

A

Did we accurately identify the causal effect we care about?
Are there factors other than the intended independent vari-
able that could be responsible for the outcome?

18
Q

External validity

A

extent to which experimental findings (specifically: causal
effects) may be generalized to other settings, measurements,
populations, and time periods

19
Q

Between subject

A

– each subject is assigned to either treatment or control upon
entering the study
– comparison is made between groups of people (and require
assumption of equivalence between groups)

20
Q

Within-subject

A

– each person serves as both treatment and control
– comparisons are made for a given person under treatment
and under control

21
Q

Factorial designs

A

An experiment in which two or more variables (factors) are
manipulated independently

22
Q

Natural experiments

A

experiments in which the intervention is
not under the control of the researcher

23
Q

Payoffs of Natural Experiments

A

much stronger causal identification than traditional
case studies or correlational (quantitative) analyses

24
Q

Types of Natural Experiments

A
  1. Randomizing device (with a known
    probability) divides a population
  2. Jurisdictional studies
    - make use of geographic divisions to study similar populations
    that find themselves by chances on opposite sides of some
    divide
  3. Omnibus (“other”) category
    - e.g., effect of bad weather on economics
25
Are Large-N or small-N better for controlling for confounding variables?
Large-N
26
Degrees of Freedom
df : # observations − (number of IVs and controls)
27
Benefits of process tracing
→ addresses causal mechanisms → addresses concerns about reverse causation
28
Four types of process-tracing tests
1. Straw-in-the-Wind 2. Hoop tests 3. Smoking Gun test 4. Doubly-decisive
29
Straw-in-the-Wind Test
Can increase plausibility of a hypothesis (or raise doubts), but are not decisive by themselves
30
Hoop Test
hypothesis must “jump through the hoop” in order to remain under consideration
31
Smoking Gun Test
provides sufficient criterion for accepting explanation, but is not necessary
32
Doubly Decisive Test
provides necessary criteria and sufficient criteria for accepting explanation (confirms one hypothesis while ruling out all others)
33
motivational biases
we not only see what we expect to see, but particularly what we want to see
34
Complexity
in a system (units/elements are interconnected), chains of consequence extend over time and many areas
35
Fraud
falsifying data
36
Spurious correlation:
a correlation that is not what it appears to be
37
P-hacking
the practice of reanalyzing data in many different ways and only presenting the preferred results
38
The garden of forking paths
The unconscious tendency of individuals to fit their processing of information to conclusions that suit some end or goal