Some Sampling Concepts
- Fundamental goal of research à generalize from sample to wider population
- Statistical generalization – use probability theory to estimate likelihood that patterns observed in sample will hold in population (relies on random samples)
- Replication – test generalisability – test in different situations
- Census
- Sample
- Sampling frame - list of population elements
- Representative sample – profile of sample same as population
- Weighting
- Sampling error
Types of Probability Samples
- Simple random sampling
o Complete sampling frame
o Requires good sampling frame, and population is geographically concentrated or data collection method does not require travelling
o Cost
- Systematic sampling
o Similar to simple random sampling
o Randomly chose start point, then choose nth unit
o Problem – periodicity of sampling frame – eg, husband & wife
- Stratified sampling
o Select stratifying variable
o Divide sampling frame into separate lists
o Randomly close sample from each list
- Multistage cluster sampling
o Final sample involves several different samples
§ Eg
· Divide city into areas (clusters)
· Select sample of areas
· Divide clusters into smaller units – sample
· For each smaller unit – list addresses – sample
· At each selected address – select individual
o Maximize number of initial clusters à increase chance of representativeness – but this increases sampling costs
o Use stratification techniques
Internet Samples
- E-mail surveys
- Web page based surveys
o Pop ups
o Advertising on other sites
o E-mail invitations
o Panels / representative panels
http://statisticsandastudent.blogspot.com/2011/02/aapor-report-on-on-line-panels.html
- Internet samples and representativeness – 3 ways to use internet to gain representative general population samples
o Connect a random sample to internet
o Multimode methods of questionnaire administration
§ Complex
§ Mode effects
o Using quota internet samples
§ Make a sample that is representative in specific respects
o Use of internet samples
Sample sizes
- Degree of accuracy
- Extent of variation in population
- Relationship between sample size and accuracy
o Small samples à small increase in sample size can lead to substantial increase in accuracy
o Size of population from which we draw sample is irrelevant
o Heterogeneous population – smaller sample à ie 90% voting one way vs 50/50 split
§ But allow flexibility in survey purpose, and go for larger sample sizes
o Sample sizes of sub groups
§ Sample size and variation within each group should determine sample size of each group
Non Response
- Problems
o Unacceptable reduction of sample size
o Bias
o Techniques to reduce non response may not avoid bias problem
§ Often non responders are different in crucial respects from responders
· Use available information on non responders
· Some sampling frames can provide useful information
o Official records
· Compare with known characteristics of population – ie census balanced
http://statisticsandastudent.blogspot.com/2011/02/chapter-1-introduction-to-survey-errors.html
Weighting Samples
- Due to
o Non response
o Deliberate oversampling
o Inadequate sampling frames
- Purpose – adjust sample so that sample profile on key variables reflects that of population
- Statistically increasing / decreasing 'numbers' of cases with particular characteristics so proportion of cases in sample is adjusted to population proportion.
- How to weight a sample on single characteristic
o Example
§ Select variable – gender
§ Obtain population and sample percentages
§ Calculate weight for each category
· Ie male
o Sample 35%
o Population 50%
· Male weight = 50 / 355 – 1.43
- How to weight a sample on two / more characteristics
Secondary Analysis
Non Probability Sampling
- Eg, to sample gays
- Purposive sampling – cases selected by researcher
- Quota sampling
- Availability samples
Sampling Checklist
GW Comments
- How does stratified sampling differ from blocking
- Cluster sampling – see article on fathers & un wed births.
http://statisticsandastudent.blogspot.com/2011/02/fragile-families-sample-design.html
- Get notes from Anova course on sample size
- Sources for : Heterogeneous population – smaller sample à ie 90% voting one way vs 50/50 split
- Non response – see notes
http://statisticsandastudent.blogspot.com/2011/02/chapter-1-introduction-to-survey-errors.html
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