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Regression Methods for Medical Research

the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are;

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Statistical Modelling for Social Researchers

This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist;

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Statistical Modelling for Social Researchers

This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist;

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R In Finance And Economics

This book provides an introduction to the statistical software R and its application with an empirical approach in finance and economics;

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Computer Intensive Statistical Methods

This book focuses on computer intensive statistical methods, such as validation, model selection, and bootstrap, that help overcome;

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Computer Intensive Statistical Methods

This book focuses on computer intensive statistical methods, such as validation, model selection, and bootstrap, that help overcome;

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Statistical Modelling in Higher Learning

presents you with a solid understanding on the predictors using classification tree mining and logistic regression analysis.Classification is the;

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Bayesian Methods for Nonlinear Classification and Regression

Classification and Regression is the first book to bring together, in a consistent statistical framework, the ideas of nonlinear modelling and Bayesian;

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Statistical Regression Modeling with R

regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume;

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Statistical Regression Modeling with R

regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume;

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Regression Modeling Strategies

when developing multi-variable models using real data and not standard textbook examples. Regression Modelling Strategies presents full;

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Regression Modeling Strategies

when developing multi-variable models using real data and not standard textbook examples. Regression Modelling Strategies presents full;

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Statistical Models of Characteristics of Metal Vapor Lasers

In this book, various multivariate statistical techniques are applied in order to assess and predict the experiment. There are developed;

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Data Analysis with Stata

management. Next, the book takes you through data visualization and all the important statistical tests in STATA. Linear and logistic regression;

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Confidence Intervals in Generalized Regression Models

generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical;

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Confidence Intervals in Generalized Regression Models

generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical;

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Flexible Bayesian Regression Modelling

econometric and statistical analysis where datasets are characterized by complexity, multiplicity, and large sample sizes, necessitating the need for;

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Robustness and Complex Data Structures

for time series and regression analysis, and with statistical methods for complex data structures. The individual contributions of leading;

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Mixed Effects Models & Extensions Ecolog

measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. The book starts by revising regression, additive;

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Machine Learning for Knowledge Discovery with R

, regularized regression, support vector machine, neural network, clustering, and causal-effect inference. Additionally, it emphasizes statistical;

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Modelling Binary Data

developments have emerged, accompanied by the steady growth of statistical computing. Mixed models for binary data analysis and procedures that lead to;

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Modelling Binary Data

developments have emerged, accompanied by the steady growth of statistical computing. Mixed models for binary data analysis and procedures that lead to;

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An Introduction to Generalized Linear Models

distributions; linear regression models; classical estimation and model fitting methods; and frequentist methods of statistical inference. After forming;

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An Introduction to Generalized Linear Models

distributions; linear regression models; classical estimation and model fitting methods; and frequentist methods of statistical inference. After forming;

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R Statistics Cookbook

Perform t-tests, chi-squared tests, and regression analysis using modern statistical techniques Book DescriptionR is a popular programming;

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Bayesian Hierarchical Models

, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview;

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Bayesian Hierarchical Models

, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview of applied;

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