• Clin. Infect. Dis. · Oct 2007

    Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies.

    • Michelle Shardell, Anthony D Harris, Samer S El-Kamary, Jon P Furuno, Ram R Miller, and Eli N Perencevich.
    • Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA.
    • Clin. Infect. Dis. 2007 Oct 1; 45 (7): 901-7.

    AbstractQuasi-experimental study designs are frequently used to assess interventions that aim to limit the emergence of antimicrobial-resistant pathogens. However, previous studies using these designs have often used suboptimal statistical methods, which may result in researchers making spurious conclusions. Methods used to analyze quasi-experimental data include 2-group tests, regression analysis, and time-series analysis, and they all have specific assumptions, data requirements, strengths, and limitations. An example of a hospital-based intervention to reduce methicillin-resistant Staphylococcus aureus infection rates and reduce overall length of stay is used to explore these methods.

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