Logo image
Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies
Journal article   Open access   Peer reviewed

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
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, Vol.45(7), pp.901-907
10/01/2007
DOI: 10.1086/521255
PMID: 17806059
url
https://doi.org/10.1086/521255View
Published (Version of record) Open Access

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.
Outcome Assessment (Health Care) - methods Regression Analysis Data Interpretation, Statistical Cross Infection - prevention & control Drug Resistance, Multiple, Bacterial Humans Control Groups Infection Control - methods Research Design

Details

Metrics

Logo image