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Analysis of complex survey data using SAS.

S R Cole1

  • 1Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School & Department of Health and Social Behavior, Harvard School of Public Health, 900 Commonwealth Avenue East, Boston, MA 02215, USA. scole@rics.bwh.harvard.edu

Computer Methods and Programs in Biomedicine
|November 21, 2000
PubMed
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This study introduces a new method for analyzing complex survey data in SAS, using weighted generalized estimating equations. This approach accounts for intricate sampling designs, offering improved accuracy over standard statistical software.

Area of Science:

  • Statistics
  • Survey Methodology
  • Data Analysis

Background:

  • Standard statistical methods often assume independent and identically distributed data.
  • These methods may not accurately reflect complex sampling designs common in surveys.
  • Existing software can fail to account for survey complexities.

Purpose of the Study:

  • To propose and validate a statistical approach for analyzing complex survey data.
  • To demonstrate the application of this method using SAS software.
  • To compare the proposed method with commonly used software for complex survey data analysis.

Main Methods:

  • Utilizing weighted generalized estimating equations (GEE) in SAS.
  • Implementing a method that explicitly addresses complex sampling designs.

Related Experiment Videos

  • Conducting limited Monte Carlo simulations to assess method performance.

    • Main Results:

    • The proposed weighted GEE approach in SAS provides a viable alternative for complex survey data.
    • Simulations indicate support for the method's validity.
    • Application example shows differences compared to standard software outputs.

    Conclusions:

    • Weighted generalized estimating equations in SAS offer a robust way to analyze complex survey data.
    • This method improves upon standard approaches by accounting for sampling design.
    • Researchers should consider this method for more accurate survey data analysis.