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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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The Statistical Analysis of Multivariate Failure Time Data

The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the;

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The Statistical Analysis of Multivariate Failure Time Data

The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the;

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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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Survival Analysis Using the Sas System

-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with;

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Survival Analysis Using SAS

-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with;

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Generalized, Linear, and Mixed Models

array of contexts. In addition, a discussion of general methods for the analysis of such models is presented with an emphasis on the method;

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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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Marginal Models

Marginal Models for Dependent, Clustered, and Longitudinal Categorical Data provides a comprehensive overview of the basic principles;

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Spatial Analysis for the Social Sciences

models that incorporate spatial heterogeneity in the effects of covariates. Spatial Analysis for the Social Sciences also examines advanced;

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Spatial Analysis for the Social Sciences

models that incorporate spatial heterogeneity in the effects of covariates. Spatial Analysis for the Social Sciences also examines advanced;

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Flexible Parametric Survival Analysis Using Stata

the modeling of time-dependent and continuous covariates and looks at how relative survival can be used to measure mortality associated with a;

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Categorical Data Analysis

with marginal models and random effects models * Two new chapters on alternative methods for binary response data, including smoothing and;

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Analysis of Messy Data, Volume III

of blocking, explore mixed models, and present a new methodology for using covariates to analyze data from nonreplicated experiments. Analysis;

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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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Statistical Learning for Big Dependent Data

Master advanced topics in the analysis of large, dynamically dependent datasets with this insightful resource Statistical Learning with;

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Advanced Time Series Data Analysis

Introduces the latest developments in forecasting in advanced quantitative data analysis This book presents advanced univariate;

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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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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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Statistical Methods for Drug Safety

the analysis of spontaneous adverse event reports, and newer approaches, such as the use of marginal structural models for controlling dynamic;

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Statistical Methods for Drug Safety

the analysis of spontaneous adverse event reports, and newer approaches, such as the use of marginal structural models for controlling dynamic;

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Event History Analysis

the entire research path required in the application of event-history analysis, from the initial problems of recording event-oriented data to;

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Regression Models for Categorical Dependent Variables Using Stata, Third Edition

categorical dependent variables are common, few texts explain how to interpret such models; this text fills the void. With the book, Long and Freese;

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Generalized Linear Models

methods of analyzing correlated binary data using latent variables. It also proposes a semiparametric method to model link functions for binary;

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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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