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Báo cáo khoa học: "Statistics review 8: Qualitative data – tests of association"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Critical Care giúp cho các bạn có thêm kiến thức về ngành y học đề tài: Statistics review 8: Qualitative data – tests of association. | Critical Care February 2004 Vol 8 No 1 Bewick et al. Review Statistics review 8 Qualitative data - tests of association Viv Bewick1 Liz Cheek1 and Jonathan Ball2 Senior Lecturer School of Computing Mathematical and Information Sciences University of Brighton Brighton UK 2Lecturer in Intensive Care Medicine St George s Hospital Medical School London UK Correspondence Viv Bewick v.bewick@brighton.ac.uk Published online 30 December 2003 Critical Care 2004 8 46-53 DOI 10.1186 cc2428 This article is online at http ccforum.com content 8 1 46 2004 BioMed Central Ltd Print ISSN 1364-8535 Online ISSN 1466-609X Abstract This review introduces methods for investigating relationships between two qualitative categorical variables. The X2 test of association is described together with the modifications needed for small samples. The test for trend in which at least one of the variables is ordinal is also outlined. Risk measurement is discussed. The calculation of confidence intervals for proportions and differences between proportions are described. Situations in which samples are matched are considered. Keywords X2 test of association Fisher s exact test McNemar s test odds ratio risk ratio Yates correction Introduction In the previous statistics reviews most of the procedures discussed are appropriate for quantitative measurements. However qualitative or categorical data are frequently collected in medical investigations. For example variables assessed might include sex blood group classification of disease or whether the patient survived. Categorical variables may also comprise grouped quantitative variables for example age could be grouped into under 20 years 20-50 years and over 50 years . Some categorical variables may be ordinal that is the data arising can be ordered. Age group is an example of an ordinal categorical variable. When using categorical variables in an investigation the data can be summarized in the form of frequencies or counts of patients in each category.