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D Birnbaum1

  • 1Applied Epidemiology, Sidney, British Columbia, Canada.

Infection Control and Hospital Epidemiology
|February 3, 2000
PubMed
Summary
This summary is machine-generated.

The Wald approximation for infection rates can yield inaccurate confidence intervals, including impossible negative values. This approximation error affects both small and large sample sizes in infection surveillance.

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Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Calculating confidence intervals for infection rates is crucial for surveillance.
  • The Wald approximation is a commonly used method for this calculation.
  • However, the Wald approximation can be inaccurate, especially with small or large sample sizes.

Purpose of the Study:

  • To highlight the limitations of the Wald approximation in calculating confidence intervals for infection rates.
  • To explain why negative confidence intervals may appear.
  • To emphasize the need for accurate statistical methods in infection surveillance.

Main Methods:

  • Review of statistical approximation formulae for binomial distribution.
  • Analysis of the Wald approximation's accuracy compared to the exact binomial distribution.

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  • Examination of error occurrence across various sample sizes.

    • Main Results:

    • The Wald approximation frequently fails to accurately represent the exact binomial distribution.
    • This inaccuracy leads to confidence intervals extending into meaningless negative values.
    • Such errors are observed in both small and large sample size scenarios.

    Conclusions:

    • The use of the Wald approximation can lead to erroneous confidence intervals for infection rates.
    • Infection surveillance relying on the Wald approximation may produce misleading data.
    • Alternative, more accurate statistical methods should be considered for reliable infection rate estimation.