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Nonlinear Models for Repeated Measurement Data

of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first;

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Measurement Error in Nonlinear Models

It's been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field;

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Mixed Effects Models for Complex Data

approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews;

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Mixed Effects Models for Complex Data

approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews;

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Radiation Risk Estimation

covers nonlinear measurement error models, with a particular emphasis on efficiency of regression parameter estimators. In the second part, risk;

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Partially Linear Models

efficient estimation, bootstrap resampling, censored data analysis, linear measurement error models, nonlinear measurement models, nonlinear and;

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Nonlinear Principal Component Analysis and Its Applications

any types of measurement levels by using nonlinear PCA. Sparseness and joint dimension reduction and clustering for nonlinear data, the;

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Measurement Error in Nonlinear Models

measurement error for the properties of nonlinear econometric estimators. It investigates the extent to which appropriate econometric techniques can;

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Bayesian Methods for Repeated Measures

the Bayesian analysis of categorical response data in a repeated measures study, Bayesian analysis for repeated measures when the mean profile;

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Bayesian Methods for Repeated Measures

the Bayesian analysis of categorical response data in a repeated measures study, Bayesian analysis for repeated measures when the mean profile;

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Time Series Modeling of Neuroscience Data

applications to signal detection problems in EEG data analysis An innovation-based method for the characterization of nonlinear and/or non-Gaussian;

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Growth Curve Modeling

growth models Nonlinear regression Yield-density curves Nonlinear mixed effects models for repeated measurements data Growth Curve Modeling;

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Methods and Applications of Longitudinal Data Analysis

generalized estimating equationsnonlinear regression models for categorical repeated measurementstechniques for;

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Principles And Practice Of Structural Equation Modelling

factor analysis--as well as more advanced methods, including the evaluation of nonlinear effects, measurement models and structural regression;

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Mixed-Effects Models in S and S-PLUS

longitudinal data, repeated measures, and multilevel data. The authors present a unified model-building strategy for both models and apply this to the;

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Mixed-Effects Models in S and S-PLUS

longitudinal data, repeated measures, and multilevel data. The authors present a unified model-building strategy for both models and apply this to the;

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SAS for Mixed Models, Second Edition

featuring the MIXED, GLIMMIX, and NLMIXED procedures in this valuable edition of the comprehensive mixed models guide for data analysis, completely;

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Measurement Error Models

The author is to be commended for providing a complete presentation of a very important topic. Statisticians working with measurement error;

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Generalized Linear and Nonlinear Models for Correlated Data

Edward F. Vonesh's "Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS" is devoted to the;

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Nonlinear Time Series Analysis

nonlinear and non-Gaussian state space models provide a much wider range of tools for time series analysis. In addition, advances in computing and;

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Univariate and Multivariate General Linear Models

, and multivariate GLMs that cover multivariate regression analysis, MANOVA, MANCOVA, and repeated measurement data analyses. The book also;

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Univariate and Multivariate General Linear Models

, and multivariate GLMs that cover multivariate regression analysis, MANOVA, MANCOVA, and repeated measurement data analyses. The book also;

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Repeated Measurements and Cross-Over Designs

An introduction to state-of-the-art experimental design approaches to better understand and interpret repeated measurement data in cross;

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Nonlinear System Techniques and Applications

practical techniques currently available for analyzing and identifying nonlinear systems from random data measured at the input and output points;

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Modelling Nonlinear Economic Time Series

the reader how to apply these models in practice. For this purpose, the building of various nonlinear models with its three stages of model;

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Dynamical Biostatistical Models

Dynamical Biostatistical Models presents statistical models and methods for the analysis of longitudinal data. The book focuses on models;

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ANOVA

By focusing on situations in which analysis of variance (ANOVA) involves the repeated measurement of separate groups of individuals, Girden;

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