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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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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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Nonparametric Regression Methods For Longitudinal Data Analysis

nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling;

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Selection Models for Nonignorable Missing Data

is developed. This approach is unique in literature. The proposed model is extended to a model for longitudinal data.;

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Longitudinal Data Analysis

Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight;

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Mixed Effects Models for Complex Data

semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values;

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Mixed Effects Models for Complex Data

semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values;

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Analysis Of Longitudinal Data

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis;

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Nonparametric Statistical Methods Using R

nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and;

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Nonparametric Statistical Methods Using R

for cluster correlated data. The book can be used as a primary text or supplement in a course on applied nonparametric or robust;

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Methods and Applications of Longitudinal Data Analysis

Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical;

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Antedependence Models for Longitudinal Data

, Antedependence Models for Longitudinal Data offers a convenient, systematic way to learn about antedependence models. Illustrated with numerous examples;

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Advanced Linear Modeling

nonparametric regression, response surface maximization, and longitudinal models. The book provides a unified approach to these disparate subjects and;

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Models for Intensive Longitudinal Data

A new class of longitudinal data has emerged with the use of technological devices for scientific data collection. This class of data;

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Frontiers In Statistics

have contributed 16 review articles and 6 research articles covering areas including semi-parametric models, data analytical nonparametric;

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Frontiers In Statistics

have contributed 16 review articles and 6 research articles covering areas including semi-parametric models, data analytical nonparametric;

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Measurement Error in Longitudinal Data

Longitudinal data is essential for understanding how the world around us changes. Most theories in the social sciences and elsewhere have a;

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Generalized Additive Models

This book describes an array of power tools for data analysis that are based on nonparametric regression and smoothing techniques. These;

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Analysis Of Longitudinal Data 2nd

The first edition of Analysis for Longitudinal Data has become a classic. Describing the statistical models and methods for the analysis;

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Longitudinal Analysis

the models to their own data The book opens with the building blocks of longitudinal analysis-general ideas, the general linear model for;

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Longitudinal Analysis

for longitudinal data Integrated model comparisons, effect sizes, and statistical inference in each example to strengthen readers;

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Nonparametric Econometric Methods

Methods', and the papers selected for inclusion in this Volume span a range of nonparametric techniques including kernel smoothing, empirical;

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Missing Data in Longitudinal Studies

Drawing from the authors' own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for;

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Longitudinal Data Analysis Using Structural Equation Models

When determining the most appropriate method for analyzing longitudinal data, you must first consider what research question you want to;

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Longitudinal Structural Equation Modeling with Mplus

- and multiple-indicator data. The book discusses measurement equivalence testing, intensive longitudinal data modeling, and missing data;

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Linear Mixed Models for Longitudinal Data

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this;

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Joint Models of Longitudinal a

-to-recurrence. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R provides a full treatment of random effects joint;

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