Analyze Repeated Measures Studies Using Bayesian TechniquesGoing beyond standard non-Bayesian books, Bayesian Methods for Repeated Measures presents the main ideas for the analysis of repeated measures and associated designs from a Bayesian viewpoint. It describes many inferential methods for analyzing repeated measures in various scientific areas,
Judge, G.G., Griffiths, W.E., Hill, R.C., Lütkepohl, H. and Lee, T.-C. (1985) The Theory and Practice of Econometrics (2nd edn). Wiley, New York. Karlsson, M.O. and Sheiner, L.B. (1994) The importance of modeling interoccasion variation ...
A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.
* A practical introduction to multilevel modelling for non-specialists * Multilevel models and repeated measures analysis throughout the book * Multiple fully worked examples of complex analyses, including code and data * Modern perspective ...
Responding to this need, Computational Methods in Biomedical Research explores important current and emerging computatio
Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin. Murray, J. S., Dunson, D. B., Carin, L., and Lucas, J. E. (2013). ... Neal, R. M. (1993). Probabilistic inference using Markov chain Monte Carlo ...
From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis Enables students to select the correct statistical methods ...
Applied Factorial and Fractional Designs , Robert A. McLean and Virgil L. Anderson 56. Design of Experiments : Ranking and Selection , edited by Thomas J. Santner and Ajit C. Tamhane 57. Statistical Methods for Engineers and Scientists ...
A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide.
Fundamental Concepts for New Clinical Trialists Scott Evans and Naitee Ting Generalized Linear Models: A Bayesian Perspective Dipak K. Dey, Sujit K. Ghosh, and Bani K. Mallick Handbook of Regression and Modeling: Applications for the ...
Both the Pearson and deviance statistics can be used for detecting observations not well fitted by the model. The deviance residuals are more commonly used because their distribution tends to be closer to normal than that of the Pearson ...