Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/43642
Type: Journal article
Title: Statistics in review; Part 1: graphics, data summary and linear models
Author: Moran, J.
Solomon, P.
Citation: Critical Care and Resuscitation, 2007; 9(1):81-90
Publisher: Australasian Academy of Critical Care Medicine
Issue Date: 2007
ISSN: 1441-2772
2652-9335
Statement of
Responsibility: 
John L Moran and Patricia J Solomon
Abstract: Statistics and biomedical literature have historically had an uneasy alliance. A critical approach to the application of statistics is developed. Initially, we survey graphical data display and trace the historical development of the "testing" statistical paradigm, and the contributions of A R Fisher and J Neyman and E Pearson. The nuances of data summary and testing are illustrated by way of population versus sample estimation. The importance of the normality assumption is stressed, and the recurring contrast of parametric (t test) versus non-parametric (Mann-Whitney) approaches to summary statistics is discussed. The t test is found to be adequate. Effect measures are outlined, and we demonstrate the utility of the unpaired t test for binary data analysis. The theory of linear models is introduced, and the underlying assumptions of the standard ordinary least squares regression are presented. The implications of transformations, in particular log transformation, are detailed, and we conclude with an overview of the principles of model selection.
Keywords: Humans
APACHE
Confidence Intervals
Data Interpretation, Statistical
Linear Models
Logistic Models
Chi-Square Distribution
Sample Size
Statistics as Topic
Controlled Clinical Trials as Topic
Rights: Copyright © 2007 Australian and New Zealand College of Anaesthetists
Appears in Collections:Aurora harvest
Mathematical Sciences publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.