conductingonlinesurveys_sue_ch3

Conducting ONL I NE SURVEYS

Valerie M. Sue, Ph.D.

Sampling 3.

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

Populations & Samples

Set of all units Population

Subset of a population Sample

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List of population members

Sampling frame

Sampling Techniques

Saturation Sampling: survey everyone (census)

Probability Sampling Participants are randomly selected

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Closed populations Simple random

Systematic

Stratified

Cluster

Open populations Intercept

Prerecruited panel

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

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

Stratified: select random samples within population subgroups

Group A Group B Group C

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

Intercept: interrupt browsing, invite every nth visitor to respond

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

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

Snowball: participants refer associates

How large should the sample be

When using simple random

samples

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

When using nonprobability

samples

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

Sources of

Coverage error: sampling frame doesn’t represent population

Nonresponse error: some selected members choose not to participate

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

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