Analysis of correlated data with SAS and R (Record no. 30092)

000 -LEADER
fixed length control field a
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200530b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781138197459
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 614.40727
Item number SHO
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Shoukri, Mohamed M.
245 ## - TITLE STATEMENT
Title Analysis of correlated data with SAS and R
250 ## - EDITION STATEMENT
Edition statement 4th ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc CRC Press
Date of publication, distribution, etc 2018
Place of publication, distribution, etc Boca Raton
300 ## - PHYSICAL DESCRIPTION
Extent xv, 497 p.
Other physical details ill.
Dimensions 25 cm.
365 ## - TRADE PRICE
Price amount 89.00
Price type code GBP
Unit of pricing 98.20
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references.
520 ## - SUMMARY, ETC.
Summary, etc "Analysis of Correlated Data with SAS and R: 4th edition presents an applied treatment of recently developed statistical models and methods for the analysis of hierarchical binary, count and continuous response data. It explains how to use procedures in SAS and packages in R for exploring data, fitting appropriate models, presenting programming codes and results. The book is designed for senior undergraduate and graduate students in the health sciences, epidemiology, statistics, and biostatistics as well as clinical researchers, and consulting statisticians who can apply the methods with their own data analyses. In each chapter a brief description of the foundations of statistical theory needed to understand the methods is given, thereafter the author illustrates the applicability of the techniques by providing sufficient number of examples. The last three chapters of the 4th edition contain introductory material on propensity score analysis, meta-analysis and the treatment of missing data using SAS and R. These topics were not covered in previous editions. The main reason is that there is an increasing demand by clinical researchers to have these topics covered at a reasonably understandable level of complexity. Mohamed Shoukri is principal scientist and professor of biostatistics at The National Biotechnology Center, King Faisal Specialist Hospital and Research Center and Al-Faisal University, Saudi Arabia. Professor Shoukris research includes analytic epidemiology, analysis of hierarchical data, and clinical biostatistics. He is an associate editor of the 3Biotech journal, a Fellow of the Royal Statistical Society and an elected member of the International Statistical Institute"--Provided by publisher.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Interpretation, Statistical
Topical term or geographic name as entry element Cluster Analysis
Topical term or geographic name as entry element Medical informatics
Topical term or geographic name as entry element Medicine - Data processing
Topical term or geographic name as entry element Mathematical statistics - Data processing
Topical term or geographic name as entry element Medical statistics
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent location Current location Date acquired Total Checkouts Full call number Barcode Date last seen Date last borrowed Koha item type
          DAIICT DAIICT 2020-05-29 1 614.40727 SHO 032292 2022-12-22 2022-05-18 Books

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