Buch, Englisch, 188 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 471 g
Buch, Englisch, 188 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 471 g
ISBN: 978-3-319-92746-6
Verlag: Springer International Publishing
Modern Bayesian statistics is based on biological likelihoods, and may better fit clinical data than traditional tests based normal distributions do. This is the first edition to systematically implymodern Bayesian statistics in traditional clinical data analysis. This edition also demonstrates that Markov Chain Monte Carlo procedures laid out as Bayesian tests provide more robust correlation coefficients than traditional tests do. It also shows that traditional path statistics are both textually and conceptionally like Bayes theorems, and that structural equations models computed from them are the basis of multistep regressions, as used with causal Bayesian networks.
Zielgruppe
Graduate
Autoren/Hrsg.
Fachgebiete
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Biomedizin, Medizinische Forschung, Klinische Studien
- Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Epidemiologie, Medizinische Statistik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Public Health, Gesundheitsmanagement, Gesundheitsökonomie, Gesundheitspolitik
- Mathematik | Informatik Mathematik Stochastik Bayesianische Inferenz
Weitere Infos & Material
Preface.- General Introduction to Modern Bayesian Statistics.- Traditional Bayes: Diagnostic Tests, Genetic Research, Bayes and Drug Trials.- Bayesian Tests for One Sample Continuous Data.- Bayesian Tests for One Sample Binary Data.- Bayesian Paired T-Tests.- Bayesian Unpaired T-Tests.- Bayesian Regressions.- Bayesian Analysis of Variance (Anova).- Bayesian Loglinear Regression.- Bayesian Poisson Rate Analysis.- Bayesian Pearson Correlations.- Bayesian Statistics: Markov Chain Monte Carlo Sampling.- Bayes and Causal Relationships.- Bayesian Network.- Index.