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*24510$aMedical statistics :$bin clinical and epidemiological research$cMarit B. Veierød, Stian Lydersen, and Petter Laake (eds.)
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*264 1$aOslo$bGyldendal akademisk$c[2020]
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*520  $aAn in-depth and up-to-date coverage of the areas of statistics at the PhD level. During the recent years, there has been a huge increase in the use of advanced statistical methods in clinical and epidemiological research. Many researchers need an understanding of statistics beyond what is covered in introductory courses. This book is intended as a course textbook in clinical and epidemiological research, as well as a reference book for students or working professionals in health sciences. It gives an in-depth and up-to-date coverage of the areas of statistics which are relevant at the PhD level in clinical and epidemiological research. The book consists of twenty chapters written by twenty-nine authors, all experts in their fields. Each chapter is self-contained and may be read independently according to the needs of the reader. The editors, Marit B. Veierød, Stian Lydersen and Petter Laake, all Professors of Medical Statistics, have extensive experience from teaching medical statistics at the Master and PhD levels, and from clinical and epidemiological research projects. The tables and figures in the book are available for downloading for educational use from the book's website, www.medicalstatistics.no. Contents: 1. Design and analysis (Marit B. Veierød, Stian Lydersen and Petter Laake) 2. Categorical data and contingency tables .. (Stian Lydersen, Morten W. Fagerland and Petter Laake) 3. Logistic regression (David W. Hosmer and Stanley Lemeshow) 4. Linear regression (Morten W. Fagerland, Geir Egil Eide and Petter Laake) 5. Survival analysis (Odd O. Aalen and Marianne Riksheim) 6. Poisson regression (Sven Ove Samuelsen and Marit B. Veierød) 7. Mixed models (Magne Thoresen and Håkon K. Gjessing) 8. Longitudinal analysis (Magne Thoresen) 9. Generalized linear latent and mixed models .. (Anders Skrondal and Sophia Rabe-Hesketh) 10. Measurement error (John P. Buonaccorsi) 11. Power and sample size (Michael Væ
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