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001			9780429061240
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005			20220531132306.0
006			m o d
007			cr |||||||||||
008			210125s2021 flua fob 001 0 eng d
040			_aOCoLC-P _beng _erda _epn _cOCoLC-P
020			_a9780429592171 _q(e-book)
020			_a0429592175
020			_a9780429061240 _q(electronic bk.)
020			_a0429061242 _q(electronic bk.)
020			_a9780429588297 _q(electronic bk. : Mobipocket)
020			_a0429588291 _q(electronic bk. : Mobipocket)
020			_a9780429590238 _q(electronic bk. : EPUB)
020			_a0429590237 _q(electronic bk. : EPUB)
020			_z9780367183837 (hbk.)
024	8		_a10.1201/9780429061240 _2doi
035			_a(OCoLC)1245418686
035			_a(OCoLC-P)1245418686
050		4	_aR853.M48
072		7	_aMAT _x029000 _2bisacsh
072		7	_aMED _x071000 _2bisacsh
072		7	_aPBT _2bicssc
082	0	4	_a610.7 _223
100	1		_aChen, Ding-Geng, _eauthor.
245	1	0	_aApplied meta-analysis with R and Stata _cDing-Geng (Din) Chen, Karl E. Peace.
250			_aSecond edition.
264		1	_aBoca Raton : _bChapman & Hall/CRC, _c2021.
300			_a1 online resource _billustrations (black and white).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	0		_aChapman & Hall/CRC biostatistics series
520			_aReview of the First Edition: The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathematics background. Unlike in many other textbooks, R is not introduced with meaningless toy examples; instead the reader is taken by the hand and shown around some analyses, graphics, and simulations directly relating to meta-analysisA useful hands-on guide for practitioners who want to familiarize themselves with the fundamentals of meta-analysis and get started without having to plough through theorems and proofs. --Journal of Applied Statistics Statistical Meta-Analysis with R and Stata, Second Edition provides a thorough presentation of statistical meta-analyses (MA) with step-by-step implementations using R/Stata. The authors develop analysis step by step using appropriate R/Stata functions, which enables readers to gain an understanding of meta-analysis methods and R/Stata implementation so that they can use these two popular software packages to analyze their own meta-data. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R/Stata packages and functions. What's New in the Second Edition: Adds Stata programs along with the R programs for meta-analysis Updates all the statistical meta-analyses with R/Stata programs Covers fixed-effects and random-effects MA, meta-regression, MA with rare-event, and MA-IPD vs MA-SS Adds five new chapters on multivariate MA, publication bias, missing data in MA, MA in evaluating diagnostic accuracy, and network MA Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R or Stata) in public health, medical research, governmental agencies, and the pharmaceutical industry.
588			_aOCLC-licensed vendor bibliographic record.
630	0	0	_aStata.
650		0	_aMeta-analysis.
650		0	_aR (Computer program language)
650		7	_aMATHEMATICS / Probability & Statistics / General _2bisacsh
650		7	_aMEDICAL / Pharmacology _2bisacsh
700	1		_aPeace, Karl E., _d1941- _eauthor.
856	4	0	_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9780429061240
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999			_c70389 _d70389