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Bootstrapping: a tool for clinical research.

J F Walsh1, M Reznikoff

  • 1Fordham University.

Journal of Clinical Psychology
|November 1, 1990
PubMed
Summary
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This study introduces bootstrap sampling for clinical research data, enabling the computation of confidence intervals for simulated values. This statistical approach allows researchers to explore topics beyond traditional methods.

Area of Science:

  • Biostatistics
  • Clinical Research Methodology

Background:

  • Traditional statistical methods may not accommodate all types of clinical research data.
  • There is a need for flexible analytical techniques in clinical studies.

Purpose of the Study:

  • To apply the bootstrap sampling technique to clinical research data.
  • To compute confidence intervals for simulated values using SAS.
  • To offer clinical researchers a method to explore topics not covered by traditional statistical analyses.

Main Methods:

  • Bootstrap sampling technique applied to clinical data.
  • Confidence intervals computed for simulated values.
  • SAS software utilized for analysis.

Main Results:

Related Experiment Videos

  • Demonstration of bootstrap sampling applicability in clinical research.
  • Successful computation of confidence intervals for simulated data.
  • Facilitation of broader research exploration.

Conclusions:

  • Bootstrap sampling provides a viable alternative for clinical data analysis.
  • This method enhances the scope of research questions addressable in clinical settings.
  • Clinical researchers can utilize this technique to overcome limitations of traditional statistical approaches.