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Informationen zum Autor Anthony Morton and Geoffrey Playford , Princess Alexandra Hospital, Brisbane, Australia Kerrie Mengersen , Science and Engineering Faculty, Queensland University of Technology, Australia Michael Whitby , Greenslopes Specialist Centre, Queensland, Australia Klappentext 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 analysis using R for the growing number of scientists in hospital departments who are responsible for producing reports, and who may have limited statistical expertise.This book explores data analysis using R and is aimed at scientists in hospital departments who are responsible for producing reports, and who are involved in improving safety. Professionals working in the healthcare quality and safety community will also find this book of interestStatistical Methods for Hospital Monitoring with R:* Provides functions to perform quality improvement and infection management data analysis.* Explores the characteristics of complex systems, such as self-organisation and emergent behaviour, along with their implications for such activities as root-cause analysis and the Pareto principle that seek few key causes of adverse events.* Provides a summary of key non-statistical aspects of hospital safety and easy to use functions.* Provides R scripts in an accompanying web site enabling analyses to be performed by the reader http://www.wiley.com/go/hospital_monitoring* Covers issues that will be of increasing importance in the future, such as, generalised additive models, and complex systems, networks and power laws. Zusammenfassung Hospitals monitoring is becoming more complex and is increasing both because staff want their data analysed and because of increasing mandated surveillance. Inhaltsverzeichnis R Libraries x R Functions xi Preface xvi Introduction 1 0.1 Overview and rationale for this book 1 0.1.1 Motivation for the book 1 0.1.2 Why R? 2 0.1.3 Other reading for R 2 0.2 What methods are covered in the book? 3 0.3 Structure of the book 4 0.4 Using R 5 0.4.1 Entering data 6 0.4.2 Dates 8 0.4.3 Exporting data 10 0.5 Further notes 11 0.6 A brief introduction to rprogs charts and figures 11 0.6.1 What if there is no date column? 18 0.7 Appendix menus 20 0.7.1 IMenu() 20 0.7.2 CCMenu() 21 1 Introduction to analysis of binary and proportion data 24 1.1 Single proportion, samples and population 24 1.1.1 Calculating the confidence interval 26 1.1.2 Comparison with an expected rate 27 1.2 Likelihood ratio (Bayes factor) & supported range 29 1.3 Confidence intervals for a series of proportions 30 1.4 Difference between two proportions 33 1.4.1 Confidence intervals 33 1.4.2 Hypothesis test 35 1.4.3 The twoproportions function 37 1.5 Introducing a Bayesian approach 39 1.6 When the data are not just one or two independent samples 39 1.6.1 More than two independent proportions 40 1.6.2 Example 1, yearly data 40 1.6.3 Example 2, hospital data 43 1.6.4 Prop test and small samples 47 1.7 Summarising stratified proportion data 48 1.8 Stratified proportion data, differences between rates 50 1.8.1 Yearly data 52 1.8.2 ...
