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101 0 $aeng
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181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aPreventing and treating missing data in longitudinal clinical trials $ea practical guide /$fCraig H. Mallinckrodt$b[electronic resource]
210  1$aCambridge :$cCambridge University Press,$d2013.
215   $a1 online resource (xviii, 165 pages) $cdigital, PDF file(s)
225 1 $aPractical guides to biostatistics and epidemiology
300   $aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
311   $a1-107-03138-9 
311   $a1-107-67915-X 
320   $aIncludes bibliographical references and index.
327   $aMachine generated contents note: Part I. Background and Setting: 1. Why missing data matter; 2. Missing data mechanisms; 3. Estimands; Part II. Preventing Missing Data: 4. Trial design considerations; 5. Trial conduct considerations; Part III. Analytic Considerations: 6. Methods of estimation; 7. Models and modeling considerations; 8. Methods of dealing with missing data; Part IV. Analyses and the Analytic Road Map: 9. Analyses of incomplete data; 10. MNAR analyses; 11. Choosing primary estimands and analyses; 12. The analytic road map; 13. Analyzing incomplete categorical data; 14. Example; 15. Putting principles into practice.
330   $aRecent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.
410  0$aPractical guides to biostatistics and epidemiology.
517 3 $aPreventing & Treating Missing Data in Longitudinal Clinical Trials
606   $aClinical trials$vLongitudinal studies
606   $aMedical sciences$xStatistical methods
606   $aRegression analysis$xData processing
615  0$aClinical trials
615  0$aMedical sciences$xStatistical methods.
615  0$aRegression analysis$xData processing.
676   $a610.72/4
700   $aMallinckrodt$b Craig H.$f1958-$01042635
801  0$bUkCbUP
801  1$bUkCbUP
906   $aBOOK
912   $a9910453087903321
996   $aPreventing and treating missing data in longitudinal clinical trials$92467023
997   $aUNINA