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A Guide to Implementing Quantitative Bias Analysis

  • Timothy L. Lash
  • Aliza K. Fink
  • Matthew P. Fox
Chapter
Part of the Statistics for Biology and Health book series (SBH)

Abstract

Estimates of association from nonrandomized epidemiologic studies are susceptible to two types of error: random error and systematic error. Random error, or sampling error, is often called chance, and decreases toward zero as the sample size increases and the data are more efficiently distributed in the categories of the adjustment variables. The amount of random error in an estimate of association is measured by its precision. Systematic error, often called bias, does not decrease toward zero as the sample size increases or with more efficient distributions in the categories of the analytic variables. The amount of systematic error in an estimate of association is measured by its validity.

Keywords

Random Error Source Population Classification Error Sunlight Exposure Bias Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Timothy L. Lash
    • 1
  • Aliza K. Fink
    • 1
  • Matthew P. Fox
    • 1
  1. 1.Boston University School of Public HealthBostonUSA

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