Amazon cover image
Image from Amazon.com

Statistical methods for hospital monitoring with R [electronic resource] / Anthony Morton, Kerrie Mengersen, Geoffrey Playford, Michael Whitby.

By: Contributor(s): Material type: TextTextSeries: Statistics in practicePublisher: Chichester, West Sussex : Wiley, 2013Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118639177
  • 1118639170
  • 9781118639160
  • 1118639162
  • 9781118639184
  • 1118639189
  • 9781118639153
  • 1118639154
  • 1118596307
  • 9781118596302
Subject(s): Genre/Form: Additional physical formats: Print version:: Statistical methods for hospital monitoring with R.DDC classification:
  • 362.11068 23
LOC classification:
  • RA971
NLM classification:
  • WX 150.1
Online resources:
Contents:
Proportion -- Risk adjustment -- Cusum and related charts for binary data -- Introduction rate and count data -- Introduction, data, limitations of aggregated count data analysis -- Arranging data by weeks, months, quarters -- Multiple antibiotic-resistant organism (MRO) prevalence -- Overview of hospital quality improvement.
Summary: Hospitals monitoring is becoming more complex and is increasing both because staff want their data analysed and because of increasing mandated surveillance. This book provides a suite of functions in R, enabling scientists and data analysts working in infection management and quality improvement departments in hospitals, to analyse their often non-independent data which is frequently in the form of trended, over-dispersed and sometimes auto-correlated time series; this is often difficult to analyse using standard office software. This book provides much-needed guidance on data analy.
Tags from this library: No tags from this library for this title. Log in to add tags.
No physical items for this record

Includes bibliographical references and index.

Proportion -- Risk adjustment -- Cusum and related charts for binary data -- Introduction rate and count data -- Introduction, data, limitations of aggregated count data analysis -- Arranging data by weeks, months, quarters -- Multiple antibiotic-resistant organism (MRO) prevalence -- Overview of hospital quality improvement.

Print version record and.publisher; resource not viewed.

Hospitals monitoring is becoming more complex and is increasing both because staff want their data analysed and because of increasing mandated surveillance. This book provides a suite of functions in R, enabling scientists and data analysts working in infection management and quality improvement departments in hospitals, to analyse their often non-independent data which is frequently in the form of trended, over-dispersed and sometimes auto-correlated time series; this is often difficult to analyse using standard office software. This book provides much-needed guidance on data analy.