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Janet L. Peacock - Oxford Handbook of Medical Statistics

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Janet L. Peacock Oxford Handbook of Medical Statistics

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A good understanding of medical statistics is essential to evaluate medical research and to choose appropriate ways of implementing findings in clinical practice. The Oxford Handbook of Medical Statistics has been written to provide doctors and medical students with a comprehensive yet concise account of this often difficult subject.Described by readers as a statistical Bible, this new edition maintains the accessibility and thoroughness of the original, and includes comprehensive updates including new sections on transitional medicine, cluster designs, and modern statistical packages. The Handbook promotes understanding and interpretation of statistical methods across a wide range of topics, from study design and sample size considerations, through t- and chi-squared tests, to complex multifactorial analyses, all using examples from published research. References and further reading are included, to allow deeper understanding on specific topics.Featuring a new chapter on how to use this book in different medical contexts, the Oxford Handbook of Medical Statistics helps readers to conduct their own research and critically appraise others work.

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Frontispiece Table A Guide to Unifactorial Statistical Methods Design or - photo 1
Frontispiece

Table: A Guide to Unifactorial Statistical Methods

Design or Aim of StudyType of Data/AssumptionsStatistical Method
This guide may be used to indicate appropriate statistical methods. It is advisable to read the details of all these tests after consulting this table.
COMPARE TWO INDEPENDENT SAMPLES
Compare 2 meansContinuous, Normal distribution, same variancet test for 2 independent samples
Compare 2 proportionsCategorical, 2 categories, all expected values greater than 5Chi-squared test
Compare 2 proportionsCategorical, 2 categories, some expected values less than 5Fishers exact test
Compare distributionsOrdinalWilcoxon 2-sample signed rank test equivalent to Mann Whitney U test
Compare time to an event (eg survival) in 2 groupsContinuousLogrank test
COMPARE SEVERAL INDEPENDENT SAMPLES
Compare several meansContinuous, Normal distribution, same varianceOne-way analysis of variance
Compare time to an event (eg survival) in several groupsContinuousLogrank test
COMPARE DIFFERENCES IN A PAIRED SAMPLE
Test mean differenceContinuous, Normal distribution for differencest test for 2 paired (matched) samples
Compare 2 paired proportionsCategorical, 2 categories (binary)McNemars test
Distribution of differencesOrdinal, symmetric distributionWilcoxon matched pairs test
Distribution of differencesOrdinalSign test
RELATIONSHIPS BETWEEN TWO VARIABLES
Test strength of linear relationship between 2 variablesContinuous, at least one has Normal distributionPearsons correlation
Test strength of relationship between 2 variablesOrdinalSpearmans rank correlation, Kendalls tau (if many ties)
Examine nature of linear relationship between 2 variablesContinuous, residuals from Normal distribution, constant varianceSimple linear regression
Test association between 2 categorical variablesCategorical, more than 2 categories for either or both variables, at least 80% of expected frequencies greater than 5Chi-squared test
Test for trend in proportionsCategorical, one variable has 2 categories and the other has several categories which are ordered, sample greater than 30Chi-squared test for trend
Oxford Handbook of
Medical Statistics
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Oxford Handbook of Medical Statistics - image 2

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Oxford University Press 2020

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First Edition published in 2011

Second Edition published in 2020

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