000			02772cam a22004098i 4500
001			22521315
003			KWUST
005			20240209091036.0
008			220417s2023 flu b 001 0 eng
010			_a 2022004141
020			_a9780367030377 _q(hardback)
020			_a9781032308487 _q(paperback)
020			_z9781003306979 _q(ebook)
040			_aLCC _beng _erda _cKWUST _dDLC
042			_apcc
050	0	0	_aR 853.S7 _b.V35 2023
082	0	0	_a610.72/4 _223/eng/20220513
100	1		_aTattar, Prabhanjan, _d1979- _eauthor.
245	1	0	_aSurvival analysis / _cPrabhanjan Narayanachar Tattar, H J Vaman.
250			_aFirst edition.
263			_a2207
264		1	_aBoca Raton, FL : _bCRC Press, _c2023.
300			_apages cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
505	0		_aLifetime data and concepts -- Core concepts -- Inference--estimation -- Inference--statistical tests -- Regression models -- Further topics in regression models -- Model selection -- Survival trees -- Ensemble survival analysis -- Neural network survival analysis -- Complementary machine learning techniques.
520			_a"Survival analysis generally deals with analysis of data arising from clinical trials. Censoring, truncation, and missing data create analytical challenges and the statistical methods and inference require novel and different approaches for analysis. Statistical properties, essentially asymptotic ones, of the estimators and tests are aptly handled in the counting process framework which is drawn from the larger arm of stochastic calculus. With explosion of data generation during the past two decades, survival data has also enlarged assuming a gigantic size. Most statistical methods developed before the millennium were based on a linear approach even in the face of complex nature of survival data. Nonparametric nonlinear methods are best envisaged in the Machine Learning school. This book attempts to cover all these aspects in a concise way. Survival Analysis offers an integrated blend of statistical methods and machine learning useful in analysis of survival data. The purpose of the offering is to give an exposure to the machine learning trends for lifetime data analysis"-- _cProvided by publisher.
650		0	_aSurvival analysis (Biometry)
650		0	_aClinical trials _xStatistical methods.
700	1		_aVaman, H. J., _eauthor.
776	0	8	_iOnline version: _aTattar, Prabhanjan _tSurvival analysis. _bFirst edition _dBoca Raton, FL : CRC Press, 2022 _z9781003306979 _w(DLC) 2022004142
906			_a7 _brip _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2lcc _cBK
999			_c2603 _d2603