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Ordered Regression Models

Estimate and Interpret Results from Ordered Regression Models Ordered Regression Models: Parallel, Partial, and Non-Parallel;

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Ordered Regression Models

Estimate and Interpret Results from Ordered Regression Models Ordered Regression Models: Parallel, Partial, and Non-Parallel;

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Simultaneous Inference in Regression

Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods;

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Simultaneous Inference in Regression

Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods;

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Confidence Intervals in Generalized Regression Models

A Cohesive Approach to Regression Models Confidence Intervals in Generalized Regression Models introduces a unified representation-the;

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Confidence Intervals in Generalized Regression Models

A Cohesive Approach to Regression Models Confidence Intervals in Generalized Regression Models introduces a unified representation-the;

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Regression Models as a Tool in Medical Research

While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the;

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Regression Models As A Tool In Medical Research

While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the;

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Regression: Models, Methods and Applications

regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal;

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Regression And Time Series Model Selection

selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including;

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Regression Analysis

The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for;

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Data Analysis Using Regression & Multi

Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied;

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Data Analysis Using Regression and Multilevel/Hierarchical Models

"Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to;

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Regression Analysis and Linear Models

As a part of statistical modeling, regression analysis is the process and technique of understanding the relationship between dependent and;

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Logistic Regression Using SAS

If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Paul;

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Advanced Regression Models with SAS and R

Advanced Regression Models with SAS and R exposes the reader to the modern world of regression analysis. The material covered by this book;

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Advanced Regression Models with SAS and R

Advanced Regression Models with SAS and R exposes the reader to the modern world of regression analysis. The material covered by this book;

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Partially Linear Models

In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing;

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Forecasting with Dynamic Regression Models

This volume presents the basic concepts and practice of building, using and interpreting single equation dynamic regression models (also;

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Bootstrap Tests For Regression Models

performance of well-known asymptotic tests for regression models. This book uses the linear regression model as a framework for introducing simulation;

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Bootstrap Tests for Regression Models

performance of well-known asymptotic tests for regression models. This book uses the linear regression model as a framework for introducing simulation;

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Regression Models

for which generalized results are preferred? Author Richard Breen provides an introduction to regression models for such data, including;

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Economic Applications of Quantile Regression

Quantile regression has emerged as an essential statistical tool of contemporary empirical economics and biostatistics. Complementing;

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Logistic Regression Using SAS

If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Paul;

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Applied Regression and Modeling

The book is divided into three parts - (1) prerequisite to regression analysis followed by a discussion on simple regression, (2) multiple;

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Economic Applications of Quantile Regression

Quantile regression has emerged as an essential statistical tool of contemporary empirical economics and biostatistics. Complementing;

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Nonlinear Statistical Models

. The three major categories of statistical models that relate dependent variables to explanatory variables are covered: univariate regression;

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