Journal Article

Statistical Analysis and Application of Quasi Experiments to Antimicrobial Resistance Intervention Studies

George M. Eliopoulos, Michelle Shardell, Anthony D. Harris, Samer S. El-Kamary, Jon P. Furuno, Ram R. Miller and Eli N. Perencevich

in Clinical Infectious Diseases

Published on behalf of Infectious Diseases Society of America

Volume 45, issue 7, pages 901-907
Published in print October 2007 | ISSN: 1058-4838
Published online October 2007 | e-ISSN: 1537-6591 | DOI: http://dx.doi.org/10.1086/521255
Statistical Analysis and Application of Quasi Experiments to Antimicrobial Resistance Intervention Studies

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  • Infectious Diseases
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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.

Journal Article.  4372 words.  Illustrated.

Subjects: Infectious Diseases ; Immunology ; Public Health and Epidemiology ; Microbiology

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