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This book provides an accessible collection of techniques for analyzing nonparametric and semiparametric regression models. Worked examples;
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An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied;
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Edition of Applied Regression Modeling delivers a concise but comprehensive treatment of the application of statistical regression analysis for;
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The SSM features worked solutions to select problems in Applied Regression Analysis and Other Multivariable Methods, 5e.;
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Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression;
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econometricians and applied economists of the twentieth and early twenty-first centuries. It comprises contributions from leading econometricians and;
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This book provides an introduction to the analysis of interaction effects in logistic regression by focusing on the interpretation of the;
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examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 . Applied Multiple Regression serves as both;
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Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied;
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a basic knowledge of elementary statistics, Applied Regression Analysis, Third Edition focuses on the fitting and checking of both linear;
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widely used earlier work, An Introduction to Regression Graphics, and Weisberg's Applied Linear Regression; incorporate the latest in statistical;
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conventional statistical techniques, Takeshi Amemiya discusses the problem of choosing estimators and compares various criteria for ranking them. He;
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"Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to;
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exciting uses for graphics in statistical analyses. Regression Graphics, one of the first graduate--level textbooks on the subject, demonstrates;
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applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related;
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applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related;
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Providing a modern treatment of regression analysis, linear models and closely related methods, this book introduces students to one of the;
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For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis;
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For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis;
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regression model in detail Illustrates concepts with applied examples to help readers understand how concepts are translated into the logistic;
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regression. The authors discuss commonly applied econometric procedures, which are useful in building regression models for economic forecasting and;
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The core methods in today's econometric toolkit are linear regression for statistical control, instrumental variables methods for the;
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A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded;
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mishandled aspects of modeling R packages for both classical and robust nonlinear regression are presented in detail in the book and on an;
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Designed for the applied practitioner, this book is a compact, entry-level guide to modeling and analyzing non-Gaussian and correlated data;
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colleges and universities, and graduate schools. Applied Linear Statistical Models is the leading text in the market. It is noted for its quality;
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and 9780471370383 Applied Statistics: Analysis of Variance and Regression, Third Edition by Ruth M. Mickey, Olive Jean Dunn, Virginia A. Clark.;
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