000 02241nam a22003377a 4500
001 sulb-eb0015703
003 BD-SySUS
005 20160405134442.0
008 120402s2013||||enk o ||1 0|eng|d
020 _a9781139381666 (ebook)
020 _z9781107031388 (hardback)
020 _z9781107679153 (paperback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 0 0 _aR853.C55
_bM3374 2013
082 0 0 _a610.72/4
_223
100 1 _aMallinckrodt, Craig H.,
_eauthor.
245 1 0 _aPreventing and Treating Missing Data in Longitudinal Clinical Trials :
_bA Practical Guide /
_cCraig H. Mallinckrodt.
246 3 _aPreventing & Treating Missing Data in Longitudinal Clinical Trials
264 1 _aCambridge :
_bCambridge University Press,
_c2013.
300 _a1 online resource (180 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 0 _aPractical Guides to Biostatistics and Epidemiology
500 _aTitle from publisher's bibliographic system (viewed on 04 Apr 2016).
520 _aRecent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.
776 0 8 _iPrint version:
_z9781107031388
830 0 _aPractical Guides to Biostatistics and Epidemiology.
856 4 0 _uhttp://dx.doi.org/10.1017/CBO9781139381666
942 _2Dewey Decimal Classification
_ceBooks
999 _c37547
_d37547