Statistical Analysis and Application of Quasi Experiments to Antimicrobial Resistance Intervention Studies
Clinical Infectious Diseases2007Vol. 45(7), pp. 901–907
Citations Over TimeTop 10% of 2007 papers
George M. Eliopoulos, Michelle Shardell, Anthony D. Harris, Samer S. El‐Kamary, Jon P. Furuno, Ram R. Miller, Eli N. Perencevich
Abstract
Quasi-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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