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Advances in Complex Function Theory (Lecture Notes in Mathematics) by W. E. Kirwan (Repost)
Matrix Mathematics - Theory, Facts, and Formulas, Second Edition
Mathematics Probability, Markov Chains, Queues, and Simulation - The Mathematical Basis of Performance Modeling
Algebraic Aspects of Cryptography (Algorithms and Computation in Mathematics) by Neal Koblitz (Repost)
Mathematics Mathematical Foundations of Computer Science 2004 [Repost]
Mathematics Mathematical Logic for Computer Science (3rd edition)
Spaces of Holomorphic Functions in the Unit Ball (Graduate Texts in Mathematics) by Kehe Zhu (Repost)
An Introduction to Ergodic Theory (Graduate Texts in Mathematics) by Peter Walters (Repost)
Mathematics Symmetry Theory in Molecular Physics with Mathematica: A new kind of tutorial book (Repost)
-Mathematics for the Physical Sciences- by Herbert S. Wilf
Mathematics for Elementary Teachers - A Conceptual Approach, 9 edition
Computer-Enabled Mathematics - Integrating Experiment and Theory in Teacher Education
How to Fold It - The Mathematics of Linkages, Origami and Polyhedra
Mathematics Engineering Analysis: Interactive Methods and Programs with FORTRAN, QuickBASIC, MATLAB, and Mathematica [Repost]
Mathematics Maverick Mathematician: The Life and Science of J.E. Moyal
African Mathematics: From Bones to Computers (repost)
Topology (Allyn and Bacon Series in Advanced Mathematics) by James Dugundji
Mathematics Fundamentals of Algebraic Modeling - An Introduction to Mathematical Modeling with Algebra and Statistics, 5 edition
Mathematics LMSST - 24 Lectures on Elliptic Curves (London Mathematical Society Student Texts) by J. W. S. Cassels
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Mathematics Meta-analysis of Binary Data Using Profile Likelihood (Interdisciplinary Statistics)
Posted on 2010-04-12
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More Meta-analysis of Binary Data Using Profile Likelihood (Interdisciplinary Statistics) Providing reliable information on an intervention effect, meta-analysis is a powerful statistical tool for analyzing and combining results from individual studies. Meta-Analysis of Binary Data Using Profile Likelihood focuses on the analysis and modeling of a meta-analysis with individually pooled data (MAIPD). It presents a unifying approach to modeling a treatment effect in a meta-analysis of clinical trials with binary outcomes. After illustrating the meta-analytic situation of an MAIPD with several examples, the authors introduce the profile likelihood model and extend it to cope with unobserved heterogeneity. They describe elements of log-linear modeling, ways for finding the profile maximum likelihood estimator, and alternative approaches to the profile likelihood method. The authors also discuss how to model covariate information and unobserved heterogeneity simultaneously and use the profile likelihood method to estimate odds ratios. The final chapters look at quantifying heterogeneity in an MAIPD and show how meta-analysis can be applied to the surveillance of scrapie. Containing new developments not available in the current literature, along with easy-to-follow inferences and algorithms, this book enables clinicians to efficiently analyze MAIPDs.
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