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Split bootstrap hierarchical modeling of antibiotics abuse in China

Bei Wang1, Yi Zheng1,2, Di Fang3

  • 1School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona.

Statistics in Medicine
|February 19, 2019
PubMed

Insights

A new split bootstrap method accurately analyzes antibiotic abuse data in China, even with small cluster sizes common in pediatric respiratory infection studies. This approach overcomes limitations of traditional methods for nested data.

Area of Science:

  • Medical Statistics
  • Public Health
  • Epidemiology

Background:

  • Antibiotic abuse in 1990s China led to increased drug resistance.
  • The World Health Organization implemented a program for children under 5 with acute respiratory tract infections.
  • Hierarchical data with small cluster sizes (2-10) pose challenges for traditional statistical methods.

Purpose of the Study:

  • To analyze treatment data from Chinese hospitals concerning antibiotic abuse.
  • To address the limitations of standard statistical methods when dealing with small cluster sizes in hierarchical data.
  • To propose a novel statistical method for analyzing such data.

Main Methods:

  • Analysis of nested, three-level hierarchical data from Chinese hospitals.
  • Application of a novel 'split bootstrap' method, combining cluster bootstrap and primary unit splitting.
  • Evaluation of the split bootstrap method as an alternative to traditional algorithms that fail to converge with small clusters.

Main Results:

  • The split bootstrap method provides accurate estimations for regression coefficients.
  • This novel method overcomes convergence issues encountered by standard algorithms with small cluster sizes.
  • The method demonstrates minimal reduction in precision while ensuring accurate analysis.

Conclusions:

  • The split bootstrap method is a viable and accurate alternative for analyzing hierarchical data with small cluster sizes.
  • This technique is particularly relevant for studies on antibiotic abuse and pediatric respiratory infections in China.
  • The findings offer a robust statistical approach to address public health challenges related to antimicrobial resistance.

Keywords:
generalized linear mixed modelsresampling schemessmall sample sizes

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