Essential medical statistics [printed text] / Betty R. Kirkwood, Author ; Jonathan A.C. Sterne, Author . - 2nd ed. . - Oxford : Blackwell Science, 2004 . - X, 501 p ; 25 cm. ISBN : 978-0-86542-871-3 : 52,95 € Languages : English ( eng)
Descriptors: |
Indexation Biometry ; Medical statistics ; Medicine ; Research ; Statistical methods ; Statistics
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Abstract: |
Essential Medical Statistics is a classic amongst medical statisticians. An introductory textbook, it presents statistics with a clarity and logic that will demystify the subject, while providing a comprehensive coverage of advanced as well as basic methods. Book overviewThe second edition of Essential Medical Statistics has been comprehensively revised and updated to include modern statistical methods and modern approaches to statistical analysis, while retaining the approachable and non-mathematical style of the first edition. The book now includes full coverage of the most commonly used regression models, multiple linear regression, logistic regression, Poisson regression and Cox regression, as well as a chapter on general issues in regression modelling. In addition, new chapters introduce more advanced topics such as meta-analysis, likelihood, bootstrapping and robust standard errors, and analysis of clustered data. Aimed at students of medical statistics, medical researchers, public health practitioners and practising clinicians using statistics in their daily work, the book is designed as both a teaching and a reference text. The format of the book is clear with highlighted formulae and worked examples, so that all concepts are presented in a simple, practical and easy-to-understand way. The second edition enhances the emphasis on choice of appropriate methods with new chapters on strategies for analysis and measures of association and impact. |
Contents note: |
Using this book -- Defining the data -- Displaying the data -- Means, standard deviations and standard errors -- The normal distribution -- Confidence interval for a mean -- Comparison of two means: confidence intervals, hypothesis tests and P-values -- Using P-values and confidence intervals to interpret the results of statistical analyses -- Comparison of means from several groups: analysis of variance -- Linear regression and correlation -- Multiple regression -- Goodness of fit and regression diagnostics -- Transformations -- Probability, risks and odds (of disease) -- Proportions and the binomial distribution -- Comparing two proportions -- Chi-squared tests for 2 x 2 and larger contingency tables -- Controlling for confounding: stratification -- Logistic regression: comparing two or more exposure groups -- Logistic regression: controlling for confounding and other extensions -- Matched studies -- Longitudinal studies, rates and the Poisson distribution -- Comparing rates -- Poisson regression -- Standardization -- Survival analysis: displaying and comparing survival patterns -- Regressional analysis of survival data -- Likelihood -- Regression modelling -- Relaxing model assumptions -- Analysis of clustered data -- Systematic reviews and meta-analysis -- Bayesian statistics -- Linking analysis to study design: summary of methods -- Calculation of required sample size -- Measurement error: assessment and implications -- Measures of association and impact -- Strategies for analysis -- Appendix: statistical tables. |
Record link: |
https://kce.docressources.info/index.php?lvl=notice_display&id=119 |
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