ConductingOnlineSurveys_Sue_ch3

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Conducting ONLI NE SURVEYS Valerie M. Sue, Ph.D.

description

Presentation to accompany chapter 3 in "Conducting Online Surveys," (Sage Pub., 2012).

Transcript of ConductingOnlineSurveys_Sue_ch3

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Conducting ONL I NE SURVEYS

Valerie M. Sue, Ph.D.

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Sampling 3.

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Learning Objectives Distinguish populations & samples 1 Identify probability sampling techniques 2 Identify nonprobability sampling techniques 3 Evaluate sample size issues 4 Explain sources of error in survey samples 5

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Populations & Samples

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Set of all units Population

Subset of a population Sample

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List of population members

Sampling frame

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Sampling Techniques

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Saturation Sampling: survey everyone (census)

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Probability Sampling Participants are randomly selected

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Closed populations Simple random

Systematic

Stratified

Cluster

Open populations Intercept

Prerecruited panel

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Simple random: every member has an equal chance of being selected

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Systematic: select first person at random, then select every nth person

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Stratified: select random samples within population subgroups

Group A Group B Group C

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Cluster: randomly select preexisting groups— everyone in selected group is surveyed

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Intercept: interrupt browsing, invite every nth visitor to respond

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Prerecrutited panel: randomly select members who have previously agreed to participate

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Nonprobability Sampling Participants are NOT randomly selected

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Convenience: surveyor selects handy group

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Volunteer opt-in: Participants self-select into the sample

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Snowball: participants refer associates

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How large should the sample be

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When using simple random

samples

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Margin of Error

90% Confidence

Level

95% Confidence

Level

99% Confidence

Level

± 5% 272 384 666

± 4% 425 600 1,040

± 3% 756 1,067 1,849

± 2% 1,702 2,401 4,160

± 1% 6,806 9,604 16,641

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When using nonprobability

samples

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Rules of thumb 30 to 500

About 10% of population

Enough for subsample analysis

10 times more than the number of variables

As large as budget allows

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Sources of

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Coverage error: sampling frame doesn’t represent population

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Nonresponse error: some selected members choose not to participate

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Sampling error: difference (due to chance) between sample statistic and population parameter

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Summary

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Choose sampling technique:

probability or nonprobability

Determine sample

size

Evaluate sources of

error

Selecting samples from populations

Coverage error Nonresponse error

Sampling error

Probability Simple random Systematic Stratified Cluster Intercept Prerecruited panel

Nonprobability Convenience Volunteer Snowball