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Who is being surveyed?
Department of Political Science and GovernmentAarhus University
September 15, 2014
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1 Review of Last Week
2 New Material to CoverTotal Survey ErrorPopulationsRepresentativenessSampling FramesSampling without a FrameSimple Random Sampling
3 Preview of Next Week
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Review of Last Week New Material to Cover Preview of Next Week
1 Review of Last Week
2 New Material to Cover
3 Preview of Next Week
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Paul Lazarsfeld (1901–1976)
Originally from Austria; spent career at ColumbiaUniversity
Pioneered the study of mass media (Princeton RadioProject)
The War of the Worlds (1938)
Created the survey panel to study radio impact
First ever election surveys: The People’s Choice(1940) and Voting (1948)
Two-step flow of influence: Personal Influence
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Criteria for Causal Inference
1 Relationship
2 Temporal precedence
3 Nonconfounding
4 Mechanism
5 Level of analysis
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Assignment for this week
1 Form groups of 3 (or so)
2 Present your research question idea(s)
3 Give feedback to your peers on the idea
4 Share some with the whole class
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Review of Last Week New Material to Cover Preview of Next Week
1 Review of Last Week
2 New Material to CoverTotal Survey ErrorPopulationsRepresentativenessSampling FramesSampling without a FrameSimple Random Sampling
3 Preview of Next Week
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Review of Last Week New Material to Cover Preview of Next Week
2 New Material to CoverTotal Survey ErrorPopulationsRepresentativenessSampling FramesSampling without a FrameSimple Random Sampling
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Total Survey Error
Envision the perfect survey!
Errors introduced in design, implementation, andanalysis
Late 20th-century survey research focused onminimizing particular sources of error
“Total Survey Error” approach is about trade-offsbetween all sources of error, costs, and time
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Review of Last Week New Material to Cover Preview of Next Week
2 New Material to CoverTotal Survey ErrorPopulationsRepresentativenessSampling FramesSampling without a FrameSimple Random Sampling
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Inference Population
We want to speak to a population
But what population is it?
Example: “The Danish population”
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Review of Last Week New Material to Cover Preview of Next Week
Inference Population
We want to speak to a population
But what population is it?
Example: “The Danish population”
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Population Census
All population units are in study
History of national censuses
Denmark 1769–1970 (sporadic)U.S. 1790 (decennial)India 1871 (decennial)
Other kinds of census
Citizen registryCommercial, medical, government records“Big data”
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Review of Last Week New Material to Cover Preview of Next Week
Population Census
All population units are in study
History of national censusesDenmark 1769–1970 (sporadic)U.S. 1790 (decennial)India 1871 (decennial)
Other kinds of census
Citizen registryCommercial, medical, government records“Big data”
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Review of Last Week New Material to Cover Preview of Next Week
Population Census
All population units are in study
History of national censusesDenmark 1769–1970 (sporadic)U.S. 1790 (decennial)India 1871 (decennial)
Other kinds of censusCitizen registryCommercial, medical, government records“Big data”
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Advantages and Disadvantages
Advantages
Perfectly representativeSample statistics are population parameters
Disadvantages
CostsFeasibilityNeed
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Review of Last Week New Material to Cover Preview of Next Week
Advantages and Disadvantages
AdvantagesPerfectly representativeSample statistics are population parameters
Disadvantages
CostsFeasibilityNeed
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Review of Last Week New Material to Cover Preview of Next Week
Advantages and Disadvantages
AdvantagesPerfectly representativeSample statistics are population parameters
DisadvantagesCostsFeasibilityNeed
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Review of Last Week New Material to Cover Preview of Next Week
2 New Material to CoverTotal Survey ErrorPopulationsRepresentativenessSampling FramesSampling without a FrameSimple Random Sampling
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Representativeness
What does it mean for a sample to be representative?
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Obtaining Representativeness
Quota sampling (common prior to the 1940s)
Simple random sampling
Advanced survey designs (discuss next week)
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Review of Last Week New Material to Cover Preview of Next Week
Obtaining Representativeness
Quota sampling (common prior to the 1940s)
Simple random sampling
Advanced survey designs (discuss next week)
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Review of Last Week New Material to Cover Preview of Next Week
Obtaining Representativeness
Quota sampling (common prior to the 1940s)
Simple random sampling
Advanced survey designs (discuss next week)
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Convenience Samples
What is a convenience sample?
Different types:
Passive/opt-inSample of convenience (not a sample per se)Sample matchingOnline panels
“Purposive” samples (common in qualitative studies)
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Review of Last Week New Material to Cover Preview of Next Week
Convenience Samples
What is a convenience sample?
Different types:Passive/opt-inSample of convenience (not a sample per se)Sample matchingOnline panels
“Purposive” samples (common in qualitative studies)
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Review of Last Week New Material to Cover Preview of Next Week
Convenience Samples
What is a convenience sample?
Different types:Passive/opt-inSample of convenience (not a sample per se)Sample matchingOnline panels
“Purposive” samples (common in qualitative studies)
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Questions about conveniencesamples?
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Review of Last Week New Material to Cover Preview of Next Week
2 New Material to CoverTotal Survey ErrorPopulationsRepresentativenessSampling FramesSampling without a FrameSimple Random Sampling
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Sampling Frames
Enumeration (listing) of all units eligible for sampleselection
Two flavors:Random sample from an ordered listSystematic sampling from a randomized list
Building a sampling frameCombine existing listsCanvass/enumerate from scratch
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Big considerations
Coverage!UndercoverageOvercoverage
What is a unit?
Clustering
Overlap between units
List maintenance
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Review of Last Week New Material to Cover Preview of Next Week
Big considerations
Coverage!UndercoverageOvercoverage
What is a unit?
Clustering
Overlap between units
List maintenance
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Review of Last Week New Material to Cover Preview of Next Week
Big considerations
Coverage!UndercoverageOvercoverage
What is a unit?
Clustering
Overlap between units
List maintenance
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Review of Last Week New Material to Cover Preview of Next Week
Big considerations
Coverage!UndercoverageOvercoverage
What is a unit?
Clustering
Overlap between units
List maintenance
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Review of Last Week New Material to Cover Preview of Next Week
Big considerations
Coverage!UndercoverageOvercoverage
What is a unit?
Clustering
Overlap between units
List maintenance
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Multi-frame Designs
Construct one sample from multiple sampling frames
E.g., “Dual-frame” (landline and mobile)
Analytically complicatedOverlap of framesSample probabilities in each frame
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Review of Last Week New Material to Cover Preview of Next Week
2 New Material to CoverTotal Survey ErrorPopulationsRepresentativenessSampling FramesSampling without a FrameSimple Random Sampling
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Sampling without a Sampling Frame
Sometimes we have a population that can besampled but not (easily) enumerated in full
Examples
Protest attendeesStreams (e.g., people buying groceries)Points in time
Population is the sampling frame
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Review of Last Week New Material to Cover Preview of Next Week
Sampling without a Sampling Frame
Sometimes we have a population that can besampled but not (easily) enumerated in full
ExamplesProtest attendees
Streams (e.g., people buying groceries)Points in time
Population is the sampling frame
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Review of Last Week New Material to Cover Preview of Next Week
Sampling without a Sampling Frame
Sometimes we have a population that can besampled but not (easily) enumerated in full
ExamplesProtest attendeesStreams (e.g., people buying groceries)
Points in time
Population is the sampling frame
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Review of Last Week New Material to Cover Preview of Next Week
Sampling without a Sampling Frame
Sometimes we have a population that can besampled but not (easily) enumerated in full
ExamplesProtest attendeesStreams (e.g., people buying groceries)Points in time
Population is the sampling frame
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Review of Last Week New Material to Cover Preview of Next Week
Sampling without a Sampling Frame
Sometimes we have a population that can besampled but not (easily) enumerated in full
ExamplesProtest attendeesStreams (e.g., people buying groceries)Points in time
Population is the sampling frame
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Rare or “hidden” populations
Big concern: coverage!
Solutions?
Snowball samplingInformant samplingTargeted samplingRespondent-driven sampling
How does RDS work?
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Review of Last Week New Material to Cover Preview of Next Week
Rare or “hidden” populations
Big concern: coverage!
Solutions?
Snowball samplingInformant samplingTargeted samplingRespondent-driven sampling
How does RDS work?
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Review of Last Week New Material to Cover Preview of Next Week
Rare or “hidden” populations
Big concern: coverage!
Solutions?Snowball samplingInformant samplingTargeted samplingRespondent-driven sampling
How does RDS work?
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Questions?
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Activity!
Work in pairs
Develop two sampling frames/sampling strategies fora population
Share with class and discuss
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Review of Last Week New Material to Cover Preview of Next Week
2 New Material to CoverTotal Survey ErrorPopulationsRepresentativenessSampling FramesSampling without a FrameSimple Random Sampling
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Simple Random Sampling (SRS)
AdvantagesSimplicity of samplingSimplicity of analysis
DisadvantagesNeed sampling frame and units without any structurePossibly expensive
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Sample Estimates from an SRS
Each unit in frame has equal probability of selection
Sample statistics are unweighted
Variances are easy to calculate
Easy to calculate sample size need for a particularvariance
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Sample mean
y =1n
n∑i=1
yi (1)
where yi = value for a unit, andn = sample size
SEy =
√(1 − f )
s2
n(2)
where f = proportion of population sampled,s2 = sample variance, andn = sample size
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Sample proportion
y =1n
n∑i=1
yi (3)
where yi = value for a unit, andn = sample size
SEy =
√(1 − f )
(n − 1)p(1 − p) (4)
where f = proportion of population sampled,p = sample proportion, andn = sample size
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Estimating sample size
Imagine we want to conduct a political pollWe want to know what percentage of the public willvote for which coalition/partyHow big of a sample do we need to make a relativelyprecise estimate of voter support?
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Estimating sample size
Var(p) = (1 − f )p(1 − p)
n − 1(5)
Given the large population:
Var(p) =p(1 − p)
n − 1(6)
Need to solve the above for n.
(7)
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Estimating sample size
Var(p) = (1 − f )p(1 − p)
n − 1(5)
Given the large population:
Var(p) =p(1 − p)
n − 1(6)
Need to solve the above for n.
n =p(1 − p)
v(p)=
p(1 − p)
SE2 (7)
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Estimating sample size
Determining sample size requires:A possible value of pA desired precision (SE)
If support for each coalition is evenly matched (p = 0.5):
n =0.5(1 − 0.5)
SE2 =0.25SE2 (8)
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Estimating sample sizeWhat precision (margin of error) do we want?
+/- 2 percentage points: SE = 0.01
n =0.250.012 =
0.250.0001
= 2500 (9)
+/- 5 percentage points: SE = 0.025
n =0.25
0.000625= 400 (10)
+/- 0.5 percentage points: SE = 0.0025
n =0.25
0.00000625= 40,000 (11)
![Page 57: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/57.jpg)
Review of Last Week New Material to Cover Preview of Next Week
Estimating sample sizeWhat precision (margin of error) do we want?
+/- 2 percentage points: SE = 0.01
n =0.250.012 =
0.250.0001
= 2500 (9)
+/- 5 percentage points: SE = 0.025
n =0.25
0.000625= 400 (10)
+/- 0.5 percentage points: SE = 0.0025
n =0.25
0.00000625= 40,000 (11)
![Page 58: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/58.jpg)
Review of Last Week New Material to Cover Preview of Next Week
Estimating sample sizeWhat precision (margin of error) do we want?
+/- 2 percentage points: SE = 0.01
n =0.250.012 =
0.250.0001
= 2500 (9)
+/- 5 percentage points: SE = 0.025
n =0.25
0.000625= 400 (10)
+/- 0.5 percentage points: SE = 0.0025
n =0.25
0.00000625= 40,000 (11)
![Page 59: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/59.jpg)
Review of Last Week New Material to Cover Preview of Next Week
Important considerations
Required sample size depends on p and SE
In large populations, population size is irrelevant
In small populations, precision is influenced by theproportion of population sampled
In anything other than an SRS, sample sizecalculation is more difficult
Much political science research assumes SRS eventhough a more complex design is actually used
![Page 60: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/60.jpg)
Review of Last Week New Material to Cover Preview of Next Week
Important considerations
Required sample size depends on p and SE
In large populations, population size is irrelevant
In small populations, precision is influenced by theproportion of population sampled
In anything other than an SRS, sample sizecalculation is more difficult
Much political science research assumes SRS eventhough a more complex design is actually used
![Page 61: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/61.jpg)
Review of Last Week New Material to Cover Preview of Next Week
Important considerations
Required sample size depends on p and SE
In large populations, population size is irrelevant
In small populations, precision is influenced by theproportion of population sampled
In anything other than an SRS, sample sizecalculation is more difficult
Much political science research assumes SRS eventhough a more complex design is actually used
![Page 62: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/62.jpg)
Review of Last Week New Material to Cover Preview of Next Week
Important considerations
Required sample size depends on p and SE
In large populations, population size is irrelevant
In small populations, precision is influenced by theproportion of population sampled
In anything other than an SRS, sample sizecalculation is more difficult
Much political science research assumes SRS eventhough a more complex design is actually used
![Page 63: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/63.jpg)
Review of Last Week New Material to Cover Preview of Next Week
Important considerations
Required sample size depends on p and SE
In large populations, population size is irrelevant
In small populations, precision is influenced by theproportion of population sampled
In anything other than an SRS, sample sizecalculation is more difficult
Much political science research assumes SRS eventhough a more complex design is actually used
![Page 64: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/64.jpg)
Review of Last Week New Material to Cover Preview of Next Week
Questions about SRS?
![Page 65: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/65.jpg)
Review of Last Week New Material to Cover Preview of Next Week
1 Review of Last Week
2 New Material to Cover
3 Preview of Next Week
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Review of Last Week New Material to Cover Preview of Next Week
Next week’s agenda
Stratified sampling
Cluster sampling
Estimates, variances, and design effects
Discuss sampling schemes in published research
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Presentations?
Burnham et al.: Mortality in Iraq
Reinisch et al.: Registry data study
Walker and Enticott: Surveying public managers
![Page 68: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/68.jpg)
Review of Last Week New Material to Cover Preview of Next Week
Assignment for next week
Find a real survey or published study based on asurvey
Figure out its population, sampling frame, and sample
Write up 0.5-1.0 pages discussing and evaluating itssampling approach
We will discuss these in class next week
![Page 69: Department of Political Science and Government Aarhus University · 1 Review of Last Week 2 New Material to Cover 3 Preview of Next Week. Review of Last Week New Material to CoverPreview](https://reader033.vdocuments.us/reader033/viewer/2022051923/6011059e8163bc7058526607/html5/thumbnails/69.jpg)