國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Methods and applications of sample s...

Kieser, Meinhard.

Methods and applications of sample size calculation and recalculation in clinical trials

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Methods and applications of sample size calculation and recalculation in clinical trialsby Meinhard Kieser.
作者:	Kieser, Meinhard.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	xiv, 396 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Clinical trialsResearch
電子資源:	https://doi.org/10.1007/978-3-030-49528-2
ISBN:	9783030495282$q(electronic bk.)

Methods and applications of sample size calculation and recalculation in clinical trials
Kieser, Meinhard.

Methods and applications of sample size calculation and recalculation in clinical trials[electronic resource] /by Meinhard Kieser. - Cham :Springer International Publishing :2020. - xiv, 396 p. :ill., digital ;24 cm. - Springer series in pharmaceutical statistics,2366-8695. - Springer series in pharmaceutical statistics..

This book provides an extensive overview of the principles and methods of sample size calculation and recalculation in clinical trials. Appropriate calculation of the required sample size is crucial for the success of clinical trials. At the same time, a sample size that is too small or too large is problematic due to ethical, scientific, and economic reasons. Therefore, state-of-the art methods are required when planning clinical trials. Part I describes a general framework for deriving sample size calculation procedures. This enables an understanding of the common principles underlying the numerous methods presented in the following chapters. Part II addresses the fixed sample size design, where the required sample size is determined in the planning stage and is not changed afterwards. It covers sample size calculation methods for superiority, non-inferiority, and equivalence trials, as well as comparisons between two and more than two groups. A wide range of further topics is discussed, including sample size calculation for multiple comparisons, safety assessment, and multi-regional trials. There is often some uncertainty about the assumptions to be made when calculating the sample size upfront. Part III presents methods that allow to modify the initially specified sample size based on new information that becomes available during the ongoing trial. Blinded sample size recalculation procedures for internal pilot study designs are considered, as well as methods for sample size reassessment in adaptive designs that use unblinded data from interim analyses. The application is illustrated using numerous clinical trial examples, and software code implementing the methods is provided. The book offers theoretical background and practical advice for biostatisticians and clinicians from the pharmaceutical industry and academia who are involved in clinical trials. Covering basic as well as more advanced and recently developed methods, it is suitable for beginners, experienced applied statisticians, and practitioners. To gain maximum benefit, readers should be familiar with introductory statistics. The content of this book has been successfully used for courses on the topic.

ISBN: 9783030495282$q(electronic bk.)

Standard No.: 10.1007/978-3-030-49528-2doiSubjects--Topical Terms:

881616
Clinical trials
--Research

LC Class. No.: R853.C55 / K54 2020

Dewey Class. No.: 610.724

Methods and applications of sample size calculation and recalculation in clinical trials
LDR:03279nmm a2200325 a 4500 001 589642
003 DE-He213
005 20210311133530.0
006 m d
007 cr nn 008maaau
008 210601s2020 sz s 0 eng d
020 $a 9783030495282$q(electronic bk.)
020 $a 9783030495275$q(paper)
024 7 $a 10.1007/978-3-030-49528-2 $2 doi
035 $a 978-3-030-49528-2
040 $a GP $c GP
041 0 $a eng
050 4 $a R853.C55 $b K54 2020
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 610.724 $2 23
090 $a R853.C55 $b K47 2020
100 1 $a Kieser, Meinhard. $3 798770
245 1 0 $a Methods and applications of sample size calculation and recalculation in clinical trials $h [electronic resource] / $c by Meinhard Kieser.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xiv, 396 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer series in pharmaceutical statistics, $x 2366-8695
520 $a This book provides an extensive overview of the principles and methods of sample size calculation and recalculation in clinical trials. Appropriate calculation of the required sample size is crucial for the success of clinical trials. At the same time, a sample size that is too small or too large is problematic due to ethical, scientific, and economic reasons. Therefore, state-of-the art methods are required when planning clinical trials. Part I describes a general framework for deriving sample size calculation procedures. This enables an understanding of the common principles underlying the numerous methods presented in the following chapters. Part II addresses the fixed sample size design, where the required sample size is determined in the planning stage and is not changed afterwards. It covers sample size calculation methods for superiority, non-inferiority, and equivalence trials, as well as comparisons between two and more than two groups. A wide range of further topics is discussed, including sample size calculation for multiple comparisons, safety assessment, and multi-regional trials. There is often some uncertainty about the assumptions to be made when calculating the sample size upfront. Part III presents methods that allow to modify the initially specified sample size based on new information that becomes available during the ongoing trial. Blinded sample size recalculation procedures for internal pilot study designs are considered, as well as methods for sample size reassessment in adaptive designs that use unblinded data from interim analyses. The application is illustrated using numerous clinical trial examples, and software code implementing the methods is provided. The book offers theoretical background and practical advice for biostatisticians and clinicians from the pharmaceutical industry and academia who are involved in clinical trials. Covering basic as well as more advanced and recently developed methods, it is suitable for beginners, experienced applied statisticians, and practitioners. To gain maximum benefit, readers should be familiar with introductory statistics. The content of this book has been successfully used for courses on the topic.
650 0 $a Clinical trials $x Research $x Methodology. $3 881616
650 1 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 274067
650 2 4 $a Biostatistics. $3 339693
650 2 4 $a Pharmaceutical Sciences/Technology. $3 338426
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Springer series in pharmaceutical statistics. $3 753654
856 4 0 $u https://doi.org/10.1007/978-3-030-49528-2
950 $a Mathematics and Statistics (SpringerNature-11649)