Cantitate/Preț
Produs

Interpreting and Visualizing Regression Models Using Stata

Autor Michael N. Mitchell
en Limba Engleză Paperback – 18 dec 2020

Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials, and piecewise), interactions of continuous predictors, categorical predictors, interactions of categorical predictors, and interactions of continuous and categorical predictors. The book also illustrates how to interpret and visualize results from multilevel models, models where time is a continuous predictor, models with time as a categorical predictor, nonlinear models (such as logistic or ordinal logistic regression), and models involving complex survey data. The examples illustrate the use of the margins, marginsplot, contrast, and pwcompare commands.

This new edition reflects new and enhanced features added to Stata, most importantly the ability to label statistical output using value labels associated with factor variables. As a result, output regarding marital status is labeled using intuitive labels like Married and Unmarried instead of using numeric values such as 1 and 2. All the statistical output in this new edition capitalizes on this new feature, emphasizing the interpretation of results based on variables labeled using intuitive value labels. Additionally, this second edition illustrates other new features, such as using transparency in graphics to more clearly visualize overlapping confidence intervals and using small sample-size estimation with mixed models. If you ever find yourself wishing for simple and straightforward advice about how to interpret and visualize regression models using Stata, this book is for you.

Citește tot Restrânge

Preț: 43319 lei

Preț vechi: 47086 lei
-8% Nou

Puncte Express: 650

Preț estimativ în valută:
8291 8641$ 6902£

Carte disponibilă

Livrare economică 16-30 decembrie
Livrare express 30 noiembrie-06 decembrie pentru 6007 lei

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781597183215
ISBN-10: 1597183210
Pagini: 610
Dimensiuni: 184 x 235 x 41 mm
Greutate: 1.28 kg
Ediția:2 ed
Editura: Stata Press
Colecția Stata Press

Public țintă

Academic, Postgraduate, and Professional Practice & Development

Cuprins

Introduction; Continuous predictors: Linear; Continuous predictors: Polynomials; Continuous predictors: Piecewise models; Continuous by continuous interactions; Continuous by continuous by continuous interactions; Categorical predictors; Categorical by categorical interactions; Categorical by categorical by categorical interactions; Linear by categorical interactions; Polynomial by categorical interactions; Piecewise by categorical interactions; Continuous by continuous by categorical interactions; Continuous by categorical by categorical interactions; Multilevel models; Time as a continuous predictor; Time as a categorical predictor; Nonlinear models; Complex survey data

Notă biografică

Michael N. Mitchell is a senior statistician working in the area of sleep research as well as working on prevention of child maltreatment with the Children’s Data Network. He is the author of three other Stata Press books—A Visual Guide to Stata Graphics, Data Management Using Stata, and Stata for the Behavioral Sciences.

Descriere

Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials, and piecewise), interactions of continuous predictors, categorical predictors, interactions of categorical predictors, and interactions of continuous and categorical predictors. The book also illustrates how to interpret and visualize results from multilevel models, models where time is a continuous predictor, models with time as a categorical predictor, nonlinear models (such as logistic or ordinal logistic regression), and models involving complex survey data. The examples illustrate the use of the margins, marginsplot, contrast, and pwcompare commands.

This new edition reflects new and enhanced features added to Stata, most importantly the ability to label statistical output using value labels associated with factor variables. As a result, output regarding marital status is labeled using intuitive labels like Married and Unmarried instead of using numeric values such as 1 and 2. All the statistical output in this new edition capitalizes on this new feature, emphasizing the interpretation of results based on variables labeled using intuitive value labels. Additionally, this second edition illustrates other new features, such as using transparency in graphics to more clearly visualize overlapping confidence intervals and using small sample-size estimation with mixed models. If you ever find yourself wishing for simple and straightforward advice about how to interpret and visualize regression models using Stata, this book is for you.