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Markov Models with Covariate Dependence for Repeated Measures

methods based on sound knowledge. In addition, there is a lack of suitable software to handle repeated measures for Markov model applications. The;

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Bayesian Methods for Repeated Measures

Analyze Repeated Measures Studies Using Bayesian Techniques Going beyond standard non-Bayesian books, Bayesian Methods for Repeated;

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Bayesian Methods for Repeated Measures

Analyze Repeated Measures Studies Using Bayesian Techniques Going beyond standard non-Bayesian books, Bayesian Methods for Repeated;

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Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials

Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials is the first book focused on the application;

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Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials

Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials is the first book focused on the application;

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Statistical Topics and Stochastic Models for Dependent Data with Applications

corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov;

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Finite Markov Processes and Their Applications

, vice president of the Romanian Academy and director of its Center for Mathematical Statistics, begins with a review of relevant aspects;

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Markov Chains And Dependability Theory

chains before focusing on dependability measures, which necessitate the study of Markov chains on a subset of states representing different user;

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Dealing with Endogeneity in Regression Models with Dynamic Coefficients

Dealing with Endogeneity in Regression Models with Dynamic Coefficients presents a unified econometric framework for dealing with the;

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Markov Chains and Decision Processes for Engineers and Managers

Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and;

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Markov Chains and Decision Processes for Engineers and Managers

Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and;

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Nonparametric Models for Longitudinal Data

Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric;

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Dynamical Biostatistical Models

for analyzing repeated measures of quantitative and qualitative variables and events history, including survival and multistate models. Most;

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Repeated Measures Design for Empirical Researchers

website with supplementary IBM SPSS data sets and programming solutions as well as additional case studies Repeated Measures Design for;

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Analysis of Repeated Measures

Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions;

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Analysis of Repeated Measures

Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions;

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Latent Markov Models for Longitudinal Data

Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data;

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Latent Markov Models for Longitudinal Data

Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data;

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Markov Chains

solutions and fast numerical algorithms for solving the captured systems. In Chapter 4, the authors present a simple hidden Markov model (HMM) with;

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Optimal Covariate Designs

experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate;

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Markov Models for Pattern Recognition

. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the;

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Analysis of Messy Data Volume 1

Several modern suggestions for multiple comparison procedures Additional examples of split-plot designs and repeated measures designs The use;

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Gibbs Measures On Cayley Trees

/>The method used for the description of Gibbs measures on Cayley trees is the method of Markov random field theory and recurrent;

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Inference for Hidden Markov Models and related Models

Inference for Hidden Markov Models and related Models is een boek van Cuvillier Verlag;

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Modeling Intraindividual Variability With Repeated Measures Data

, professionals, and students working with repeated measures data from the social and behavioral sciences, business, or biological sciences.;

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Modeling Intraindividual Variability With Repeated Measures Data

, professionals, and students working with repeated measures data from the social and behavioral sciences, business, or biological sciences.;

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Mixture and Hidden Markov Models with R

This book discusses mixture and hidden Markov models for modeling behavioral data. Mixture and hidden Markov models are statistical models;

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