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Correlated Data Analysis

This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the;

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Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates

This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent;

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Generalized Linear and Nonlinear Models for Correlated Data

analysis of correlated response data using SAS, with special emphasis on applications that require the use of generalized linear models or;

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Periodically Correlated Random Sequences

as well as data sets and programs written in MATLAB(r) for performing time series analysis on data that may have a PC structure Periodically;

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Modeling Binary Correlated Responses using SAS, SPSS and R

Statistical tools to analyze correlated binary data are spread out in the existing literature. This book makes these tools accessible to;

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Advances and Challenges in Parametric and Semi-Parametric Analysis for Correlated Data: Proceedings of the 2015 International Symposium in Statistics

-parametric analysis for correlated data in both continuous and discrete setups. Thus, as a reflection of the theme of the symposium, the eight;

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Principal Component Analysis

analysis in data analysis. Principal component analysis involves a statistical procedure which orthogonally transforms a set of possibly correlated;

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Generalized Linear Models and Correlated Data Methods

Offers a unified discussion of generalized linear models and correlated data methods Provides information suitable for graduate non;

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Principal Component Analysis Handbook

This book on Principal component analysis (PCA) is a significant contribution to the field of data analysis. PCA involves a statistical;

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Analysis of Correlated Data with SAS and R

Analysis of Correlated Data with SAS and R: 4th edition presents an applied treatment of recently developed statistical models and methods;

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Analysis of Correlated Data with SAS and R

Analysis of Correlated Data with SAS and R: 4th edition presents an applied treatment of recently developed statistical models and methods;

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Generalized Linear and Nonlinear Models for Correlated Data

analysis of correlated response data using SAS, with special emphasis on applications that require the use of generalized linear models or;

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Global Seismicity Dynamics and Data Driven Science

The recent explosion of global and regional seismicity data in the world requires new methods of investigation of microseismicity and;

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Global Seismicity Dynamics and Data Driven Science

The recent explosion of global and regional seismicity data in the world requires new methods of investigation of microseismicity and;

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Modeling Survival Data

multiplecorrelated event data using marginal and random effects. The focus is on actual data examples, the analysis and interpretation of results;

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Sharing of Probabilistically Correlated Data in Peer-To-Peer Networks

organization supporting correlated data access is necessary and crucial for efficient processing, as network usage is minimized. We aim at applying;

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Common Errors In Statistics (And How To Avoid Them)

interpretations and confidence intervals; counts and correlated data; model building and testing; Bayes' Theorem; bootstrap and permutation tests; and;

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Statistical Modelling of Complex Correlated and Clustered Data Household Surveys in Africa Research Methodology and Data Analysis

widespread availability of public health data resulted in more reported epidemiological studies in literature. However, analysis of secondary data;

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Geostatistical Functional Data Analysis

Geostatistical Functional Data Analysis Explore the intersection between geostatistics and functional data analysis with this insightful;

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Logistic Regression

13 - Other Approaches for Analysis of Correlated Data. Chapters 9 and 10 extend logistic regression to response variables that have more than;

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Handbook for Applied Modeling

Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data;

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Bayesian Ideas And Data Analysis

regression, analysis of variance, and Poisson regression, before extending these methods to handle correlated data. The authors also examine survival;

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Statistical Methods in Psychiatry and Related Fields

approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and;

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Statistical Methods in Psychiatry and Related Fields

-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods;

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Fundamental Statistical Methods for Analysis of Alzheimer's and Other Neurodegenerative Diseases

A statistics textbook that delivers essential data analysis techniques for Alzheimer's and other neurodegenerative diseases. Alzheimer's;

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Handbook for Applied Modeling

Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data;

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Analysis of Longitudinal Data with Examples

introduce students and practicing statisticians to the updated methods on correlated data inference. This book will present a discussion of the;

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