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Regression Diagnostics

With Regression Diagnostics, researchers now have an accessible explanation of the techniques needed for exploring problems that compromise;

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Regression Diagnostics

Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure;

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Regression Diagnostics

Provides practicing statisticians and econometricians with new tools for assessing quality and reliability of regression estimates;

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Sensitivity Analysis in Linear Regression

This volume treats linear regression diagnostics as a tool for the application of linear regression models to real-life data. The;

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Solutions Manual to accompany Modern Regression Methods, 2e

Over the years, I have had the opportunity to teach several regression courses, and I cannot think of a better undergraduate text than this;

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Plots, Transformations, and Regression

`Repression diagnostics are a collection of methods used to find (diagnose) unusual features in a regression problem. `Although informal;

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Linear Regression Analysis

. Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis;

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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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Doing Meta-Analysis with R

, including pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for;

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Applied Linear Regression 4th Ed

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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Regression Analysis by Example

Praise for the Fourth Edition: This book is ...an excellent source of examples for regression analysis. It has been and still is readily;

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Transformation and Weighting in Regression

This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability;

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Transformation and Weighting in Regression

This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability;

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Multiple-Regression in Behavioral Research

Multiple Regression in Behavioral Research adopts a data-analysis approach to multiple regression. Pedhazur integrates design and analysis;

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Regression Analysis and Linear Models

Emphasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and;

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Statistical Methods For Health Care Research

12. New material on regression diagnostics has been added. ;

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Festschrift in Honor of R. Dennis Cook

of statistical disciplines ranging from experimental design and population genetics, to statistical diagnostics and all areas of regression-related;

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Robust Regression And Outlier Detection

student, because it emphasizes both the philosophy and practice of robustness in regression settings, and it provides excellent examples;

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Identifiability and Regression Analysis of Biological Systems Models: Statistical and Mathematical Foundations and R Scripts

robust regression analysis of complex dynamical models. The book first provides a definition of complexity in dynamic systems by introducing;

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Survival Analysis Using S

course in probability and statistics, and a course in applied linear regression models. No prior knowledge of S or R is assumed. A wide choice;

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Diagnostic Pathology, An Issue of Veterinary Clinics: Food Animal Practice

The latest information on diagnostic pathology for the food animal practitioner! Topics include resp;...

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Regression Analysis with R

Build effective regression models in R to extract valuable insights from real data Key Features Implement different regression analysis;

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Computational Statistics

knowledge of statistics and computing. This introduction covers one-sample analysis and distribution diagnostics, regression, two-sample problems;

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Regression Models for Categorical Dependent Variables Using Stata

Although regression models for categorical dependent variables are common, few texts explain how to interpret such models. Regression;

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Regression Modeling: Methods, Theory, and Computation with SAS

Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques;

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Regression Modeling: Methods, Theory, and Computation with SAS

Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques;

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Econometrics by Example

on Quantile Regression Modeling and Multivariate Regression Models. - Two further additional chapters on hierarchical linear regression;

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