E-Book, Englisch, 475 Seiten, eBook
Cleophas / Zwinderman Regression Analysis in Medical Research
2. Auflage 2021
ISBN: 978-3-030-61394-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
for Starters and 2nd Levelers
E-Book, Englisch, 475 Seiten, eBook
ISBN: 978-3-030-61394-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Regression analysis of cause effect relationships is increasingly the core of medical and health research. This work is a 2nd edition of a 2017 pretty complete textbook and tutorial for students as well as recollection / update bench and help desk for professionals.
It came to the authors' attention, that information of history, background, and purposes, of the regression methods addressed were scanty. Lacking information about all of that has now been entirely covered.
The editorial art work of the first edition, however pretty, was less appreciated by some readerships, than were the original output sheets from the statistical programs as used. Therefore, the editorial art work has now been systematically replaced with original statistical software tables and graphs for the benefit of an improved usage and understanding of the methods.In the past few years, professionals have been flooded with big data. The Covid-19 pandemic gave cause for statistical software companies to foster novel analytic programs better accounting outliers and skewness. Novel fields of regression analysis adequate for such data, like sparse canonical regressions and quantile regressions, have been included.
Zielgruppe
Graduate
Autoren/Hrsg.
Weitere Infos & Material
PrefaceChapter 1. Continuous Outcome Regressions Chapter 2. Dichotomous Outcome Regressions Chapter 3. Confirmative Regressions Chapter 4. Dichotomous Regressions Other than Logistic and Cox Chapter 5. Polytomous Outcome Regressions Chapter 6. Time to Event Regressions other than Traditional Cox Chapter 7. Analysis of Variance (ANOVA) Chapter 8. Repeated Outcomes Regression Methods Chapter 9. Methodologies for Better Fit of Categorical Predictors Chapter 10. Laplace Regressions, Multi- instead of Mono-Exponential Models Chapter 11. Regressions For Making Extrapolations. Chapter 12. Standardized Regression Coefficients Chapter 13. Multivariate Analysis of Variance and Canonical Regression Chapter 14. More on Poisson Regressions Chapter 15. Regression Trend Testing Chapter 16. Optimal Scaling and Automatic Linear Regression Chapter 17. Spline Regressions Chapter 18. More on Nonlinear Regressions Chapter 19. Special Forms of Continuous Outcome RegressionsChapter 20. Regressions for Quantitative Diagnostic Testing Chapter 21. Regressions, a Panacee or at Least a Widespread Help for Data Analyses Chapter 22. Regression Trees Chapter 23. Regressions with Latent Variables Chapter 24. Partial Correlations Chapter 25. Functional Data Analysis Basis Chapter 26. Functional Data Analysis Advanced Chapter 27. Quantile Regression Index




