New Developments In Statistical Modeling Inference And Application
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New Developments in Statistical Modeling, Inference and Application
The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking, and innovative clinical trial design and analysis. Each paper was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. It offered 3 keynote speeches, 7 short courses, 76 parallel scientific sessions, student paper sessions, and social events.
Statistical Models and Causal Inference
Author: David A. Freedman
language: en
Publisher: Cambridge University Press
Release Date: 2010
David A. Freedman presents a definitive synthesis of his approach to statistical modeling and causal inference in the social sciences.
Model Based Inference in the Life Sciences
Author: David R. Anderson
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-12-22
This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.