tailieunhanh - Báo cáo y học: "Statistics review 5: Comparison of means"

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 y học đề tài: Statistics review 5: Comparison of means. | Critical Care October 2002 Vol 6 No 5 Whitley and Ball Review Statistics review 5 Comparison of means Elise Whitley1 and Jonathan Ball2 1 Lecturer in Medical Statistics University of Bristol Bristol UK 2Lecturer in Intensive Care Medicine St George s Hospital Medical School London UK Correspondence Editorial Office Critical Care editorial@ Published online 12 July 2002 Critical Care 2002 6 424-428 This article is online at http content 6 5 424 2002 BioMed Central Ltd Print ISSN 1364-8535 Online ISSN 1466-609X Abstract The present review introduces the commonly used t-test used to compare a single mean with a hypothesized value two means arising from paired data or two means arising from unpaired data. The assumptions underlying these tests are also discussed. Keywords comparison of two means paired and unpaired data t test Previous reviews in this series have introduced the principals behind the calculation of confidence intervals and hypothesis testing. The present review covers the specific case of comparing means in rather more detail. Comparison of means arises in many different formats and there are various methods available for dealing with each of these. Some of the simpler cases are covered in this review namely comparison of a single observed mean with some hypothesized value comparison of two means arising from paired data and comparison of two means from unpaired data. All of these comparisons can be made using appropriate confidence intervals and t-tests as long as certain assumptions are met see below . Future reviews will introduce techniques that can be used when the assumptions of the t-test are not valid or when the comparison is between three or more groups. Of the three cases covered in this review comparison of means from unpaired data is probably the most common. However the single mean and paired data cases are introduced first because the t-test in these cases is more straightforward. Comparison of a single mean with a

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