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Preventing and treating missing data...

Mallinckrodt, Craig H., (1958-)

Preventing and treating missing data in longitudinal clinical trials :a practical guide /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Preventing and treating missing data in longitudinal clinical trials :Craig H. Mallinckrodt.
Reminder of title:	a practical guide /
Author:	Mallinckrodt, Craig H.,
Published:	Cambridge :Cambridge University Press,2013.
Description:	xviii, 165 p. :ill. ;26 cm.
Subject:	Clinical trialsEvaluation.
Online resource:	http://assets.cambridge.org/97811070/31388/cover/9781107031388.jpg
ISBN:	9781107679153 (pbk.) :

Preventing and treating missing data in longitudinal clinical trials :a practical guide /
Mallinckrodt, Craig H.,1958-

Preventing and treating missing data in longitudinal clinical trials :a practical guide /Craig H. Mallinckrodt. - Cambridge :Cambridge University Press,2013. - xviii, 165 p. :ill. ;26 cm. - Practical guides to biostatistics and epidemiology.

Includes bibliographical references (p. 153-159) and index.

Machine 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.

"Recent 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"--

ISBN: 9781107679153 (pbk.) :NT$984

LCCN: 2012038442Subjects--Topical Terms:

393833
Clinical trials
--Evaluation.

LC Class. No.: R853.C55 / M3374 2013

Dewey Class. No.: 610.72/4

Preventing and treating missing data in longitudinal clinical trials :a practical guide /
LDR:02550cam a2200289 a 4500 001 427328
003 DLC
005 20130502152934.0
008 140917s2013 enka b 001 0 eng
010 $a 2012038442
020 $a 9781107679153 (pbk.) : $c NT$984
020 $a 110767915X (pbk.)
020 $a 9781107031388 (hbk.)
020 $a 1107031389 (hbk.)
035 $a 2012038442
040 $a DLC $b eng $c DLC $d DLC
042 $a pcc
050 0 0 $a R853.C55 $b M3374 2013
082 0 0 $a 610.72/4 $2 23
084 $a MED090000 $2 bisacsh
100 1 $a Mallinckrodt, Craig H., $d 1958- $3 671309
245 1 2 $a Preventing and treating missing data in longitudinal clinical trials : $b a practical guide / $c Craig H. Mallinckrodt.
260 $a Cambridge : $b Cambridge University Press, $c 2013.
300 $a xviii, 165 p. : $b ill. ; $c 26 cm.
490 0 $a Practical guides to biostatistics and epidemiology
504 $a Includes bibliographical references (p. 153-159) and index.
505 8 $a Machine 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.
520 $a "Recent 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"-- $c Provided by publisher.
650 0 $a Clinical trials $v Evaluation. $3 393833
650 0 $a Medical sciences $x Statistical methods. $3 224648
650 0 $a Regression analysis $x Data processing. $3 183757
650 7 $a MEDICAL / Biostatistics. $2 bisacsh $3 671310
856 4 2 $3 Cover image $u http://assets.cambridge.org/97811070/31388/cover/9781107031388.jpg