Savitribai Phule Pune University, Pune

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Linear regression models : (Record no. 411475)

MARC details
000 -LEADER
fixed length control field 03444nam a22002657a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220901134623.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220510b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780367753665 (pbk)
040 ## - CATALOGING SOURCE
Transcribing agency JKRC
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Edition number 23
Classification number 519.536
Item number HOF
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Hoffmann, John P.
Relator term Author
9 (RLIN) 1197
245 ## - TITLE STATEMENT
Title Linear regression models :
Remainder of title applications in R /
Statement of responsibility, etc. by John P Hoffmann
250 ## - EDITION STATEMENT
Edition statement 1st
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. [Place of publication not identified] :
Name of publisher, distributor, etc. Chapman and Hall/CRC,
Date of publication, distribution, etc. 2021.
300 ## - PHYSICAL DESCRIPTION
Extent xvi, 420 p.
Dimensions 24 cm
365 ## - TRADE PRICE
Price amount 59.99
Currency code Pounds
490 ## - SERIES STATEMENT
Series statement Chapman & Hall statistics in social and behavioral sciences
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc. Research in social and behavioral sciences has benefited from linear regression models (LRMs) for decades to identify and understand the associations among a set of explanatory variables and an outcome variable. Linear Regression Models: Applications in R provides you with a comprehensive treatment of these models and indispensable guidance about how to estimate them using the R software environment. After furnishing some background material, the author explains how to estimate simple and multiple LRMs in R, including how to interpret their coefficients and understand their assumptions. Several chapters thoroughly describe these assumptions and explain how to determine whether they are satisfied and how to modify the regression model if they are not. The book also includes chapters on specifying the correct model, adjusting for measurement error, understanding the effects of influential observations, and using the model with multilevel data. The concluding chapter presents an alternative model⁰́₄logistic regression⁰́₄designed for binary or two-category outcome variables. The book includes appendices that discuss data management and missing data and provides simulations in R to test model assumptions. Features Furnishes a thorough introduction and detailed information about the linear regression model, including how to understand and interpret its results, test assumptions, and adapt the model when assumptions are not satisfied. Uses numerous graphs in R to illustrate the model⁰́₉s results, assumptions, and other features. Does not assume a background in calculus or linear algebra, rather, an introductory statistics course and familiarity with elementary algebra are sufficient. Provides many examples using real-world datasets relevant to various academic disciplines. Fully integrates the R software environment in its numerous examples. The book is aimed primarily at advanced undergraduate and graduate students in social, behavioral, health sciences, and related disciplines, taking a first course in linear regression. It could also be used for self-study and would make an excellent reference for any researcher in these fields. The R code and detailed examples provided throughout the book equip the reader with an excellent set of tools for conducting research on numerous social and behavioral phenomena. John P. Hoffmann is a professor of sociology at Brigham Young University where he teaches research methods and applied statistics courses and conducts research on substance use and criminal behavior.
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term Regression analysis -- Computer programs.
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term R (Computer program language)
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term R (Langage de programmation)
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Books
Edition 23
Suppress in OPAC No
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Cost, normal purchase price Inventory number Total Checkouts Full call number Barcode Date last seen Date last checked out Price effective from Koha item type Public note
          Jayakar Knowledge Resource Centre Jayakar Knowledge Resource Centre 29/03/2022 Universal Book Service 163 / 26.02.2022 59.99 506516 1 B2813 Q2 506516 26/03/2025 22/03/2025 10/05/2022 Books 59.99 Pounds

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