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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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Regression Models

introduced and other regression models for non-continuous dependent variables, such as the ordered probit. Concluding with an exploration of some;

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Logistic Regression Using SAS

, ordered logit analysis, discrete-choice analysis, and Poisson regression. Other highlights include discussions on how to use the GENMOD procedure;

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Applied Logistic Regression Analysis

Updated coverage of unordered and ordered polytomous logistic regression models.;

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Logistic Regression Models

Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially;

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Logistic Regression Models

Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially;

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Logistic Regression Using SAS

, ordered logit analysis, discrete-choice analysis, and Poisson regression. Other highlights include discussions on how to use the GENMOD procedure;

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Regression Models for Categorical Dependent Variables Using Stata

-truncated negative binomial models, the hurdle model for counts, the stereotype logistic regression model, the rank-ordered logit model, and the;

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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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Statistical Modelling for Social Researchers

. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic;

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Statistical Modelling for Social Researchers

. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic;

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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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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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Correlation And Regression Analysis

It is no exaggeration to say that virtually all quantitative research in the social sciences is done with correlation and regression;

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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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