Concordance Correlation Coefficient
Download Concordance Correlation Coefficient PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Concordance Correlation Coefficient book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Computational and Statistical Approaches to Genomics
Author: Wei Zhang
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-12-26
The 2nd edition of this book adds 8 new contributors to reflect a modern cutting edge approach to genomics. The expanded scope includes coverage of statistical issues on single nucleotide polymorphism analysis array, CGH analysis, SAGE analysis, gene shaving and related methods for microarray data analysis, and cross-hybridization issues on oligo arrays. The authors of the 17 original chapters have updated the contents of their chapters, including references, on such topics as the development of novel engineering, statistical and computational principles, as well as methods, models, and tools from these disciplines applied to genomics.
Encyclopedia of Research Design
"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.
Multivariate Concordance Correlation Coefficient
In many clinical studies, the Lin's concordance correlation coefficient (CCC) is a common tool to assess the agreement of a continuous response measured by two raters or methods. However, the need of measures of agreement may arise for more complex situations, such as when the responses are measured on more than one occasion by each rater or method. In this work, we propose a new CCC in the presence of repeated measurements, called the multivariate concordance correlation coefficient. We constructed the multivariate CCC based on a matrix that possesses the properties needed to characterize the level of agreement between two p x 1 vectors of random variables. For ease of interpretation, we transformed this matrix to a scalar whose value is scaled to range between -1 and 1 by using three distinct functions, namely trace, highest eigenvalue, and determinant. It can be shown that the multivariate CCC reduces to Lin's CCC when p = 1. For inference, we proposed an asymptotically unbiased estimator based on U-statistics and derived its asymptotic distribution for each form of the function. The proposed estimators are proven to be asymptotically normal and their performances are evaluated via simulation studies. To obtain a confidence interval or a test statistic, we considered a sample moment estimator of the asymptotic variance and the Z-transformation to improve the normal approximation and bound the confidence limits. The simulation studies confirmed that overall in terms of accuracy, precision, and the coverage probabilities, the estimator of the multivariate CCC based on the determinant function works relatively well in general cases even with small samples. However, for a skewed underlying distribution with moderate or weaker correlation between the two variables, the trace multivariate CCC is slightly more robust. Finally, We used real data from an Asthma Clinical Research Network(ACRN) study and the Penn State Young Women's Health Study for demonstration.