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Secondary Analysis of Large Survey Database
Author Bio
Why Conduct Secondary Anaylsis
Currently Selected Section: Advantages of Survey Data
Avoiding the Pitfalls
Start with the Research Question
Determine Variables of Interest
Identify and Evaluate the Data Source
Get the Data
Survey Design
Sampling Frame
Telephone Surveys
Followback Surveys
Multistage Cluster Samples
What is a Panel Design
Mode of Survey Administration
Survey Instruments
CodeBooks
Online Exploratory Analysis
Potential Sources of Error
Cultural Nonequivalence
Analysis of Survey Data
Cluster and Stratified Samples
Using Sample Weights
Missing Data
Power Calculations
Linking Data Sources
Multiple Comparisons
Getting Help
Giving Feedback
Conclusion
          

There are a number of advantages doing research using secondary analyses of survey data, including:

  • Generalizability of findings;
  • Timeliness (data have already been collected); and
  • Lower cost (relative to the collection of primary data).

Large sample size and inclusion of a large number of variables in these surveys often provide the statistical power to assess multiple clinical and non-clinical factors associated with functional status and symptom severity (in cross sectional studies), and health outcomes (in longitudinal studies). Survey data also allow the study of variation in outcomes and experiences with care for population subgroups (e.g. elderly, disabled, socio-economically disadvantaged), by geography (e.g. region, urban/rural), or by delivery system characteristics (e.g. managed care vs. fee-for-service; primary care vs. specialty care). Longitudinal data are used to develop predictive models. Furthermore, the investigator can derive reliable national estimates when using surveys of nationally representative population samples. Finally, Institutional Review Board (IRB) approval is, in general, less onerous for studies using secondary data, as long as researchers protect privacy and confidentiality.

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