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 到查詢結果 [ subject:"Statistics and Computing/Statistics Programs." ]

切換: 標籤 | MARC模式 | ISBD

Analysis of safety data of drug tria...

Cleophas, Ton J.

Analysis of safety data of drug trialsan update /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Analysis of safety data of drug trialsby Ton J. Cleophas, Aeilko H. Zwinderman.
其他題名:	an update /
作者:	Cleophas, Ton J.
其他作者:	Zwinderman, Aeilko H.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xi, 217 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	DrugsTesting.
電子資源:	https://doi.org/10.1007/978-3-030-05804-3
ISBN:	9783030058043$q(electronic bk.)

Analysis of safety data of drug trialsan update /
Cleophas, Ton J.

Analysis of safety data of drug trialsan update /[electronic resource] :by Ton J. Cleophas, Aeilko H. Zwinderman. - Cham :Springer International Publishing :2019. - xi, 217 p. :ill., digital ;24 cm.

Preface -- General Introduction -- Significant and Insignificant Adverse Effect -- Incidence Ratios and Reporting Ratios of Adverse Effects -- Safety Analysis and the Alternative Hypothesis -- Forest Plots of Adverse Effects -- Graphics of Adverse Effects -- Repeated Measures Methods for Testing Adverse Effects -- Benefit Risk Ratios -- Equivalence, Non-inferiority and Superiority Testing of Adverse Effects -- Part II The Analysis of Dependent Adverse Effects -- Independent and Dependent Adverse Effects. Categorical Predictors Assessed as Dependent Adverse Effects. Adverse Effect of the Dependent Type in Crossover Trial -- Confoundings and Interactions Assessed as Dependent Adverse Effects -- Subgroup Characteristics Assessed as Dependent Adverse Effects -- Random Effects Assessed as Dependent Adverse Effects -- Outliers Assessed as Dependent Adverse Effects -- Index.

The authors, as professors in statistics at various universities in Europe, are worrried about the poor quality of safety data analysis of clinical trials, despite its importance in drug development and pharmacovigilance. Clinical trials, not adequately addressing safety, are unethical. An effective approach for the purpose is to present summaries of prevalences. In order to estimate the probability, that the differences between treatment and control group did not occur merely by chance, a statistical test can be performed. This pretty crude method has recently be supplemented with better sensitive methodologies, based on machine learning clusters and networks, and multivariate analyses. Another important novelty with safety data analysis is the new insights into hypothesis testing, favoring the alternative hypotheses instead of the null hypotheses. Finally the issue of dependency is addressed. Adverse effects may be either dependent or independent of the main outcome. Dependent adverse effect are dependent not only on the treatment modalities, but also on the outcome of the trials. Random heterogeneities, outliers, confounders, interaction factors are common in clinical trials, and all of them can be considered kinds of adverse effects of the dependent type. Random regressions and analyses of variance, high dimensional clusterings, partial correlations, structural equations models, and other Bayesian methods are helpful for their analysis. The current edition was particularly written for medical and health professionals and students. It provides examples of modern analytic methods so far largely unused. All of the 16 chapters have two core characteristics, first they are for current usage, second they try and tell what readers need to know in order to understand the methods. Step by step analyses are given and self-assessment examples are supplied. Each chapter can be studied as a stand-alone.

ISBN: 9783030058043$q(electronic bk.)

Standard No.: 10.1007/978-3-030-05804-3doiSubjects--Topical Terms:

183737
Drugs
--Testing.

LC Class. No.: RM301.27 / .C546 2019

Dewey Class. No.: 615.7040287

Analysis of safety data of drug trialsan update /
LDR:03809nmm a2200325 a 4500 001 553543
003 DE-He213
005 20190827132035.0
006 m d
007 cr nn 008maaau
008 191112s2019 gw s 0 eng d
020 $a 9783030058043$q(electronic bk.)
020 $a 9783030058036$q(paper)
024 7 $a 10.1007/978-3-030-05804-3 $2 doi
035 $a 978-3-030-05804-3
040 $a GP $c GP
041 0 $a eng
050 4 $a RM301.27 $b .C546 2019
072 7 $a MBGR $2 bicssc
072 7 $a MED000000 $2 bisacsh
072 7 $a MBGR $2 thema
082 0 4 $a 615.7040287 $2 23
090 $a RM301.27 $b .C628 2019
100 1 $a Cleophas, Ton J. $3 261387
245 1 0 $a Analysis of safety data of drug trials $h [electronic resource] : $b an update / $c by Ton J. Cleophas, Aeilko H. Zwinderman.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xi, 217 p. : $b ill., digital ; $c 24 cm.
505 0 $a Preface -- General Introduction -- Significant and Insignificant Adverse Effect -- Incidence Ratios and Reporting Ratios of Adverse Effects -- Safety Analysis and the Alternative Hypothesis -- Forest Plots of Adverse Effects -- Graphics of Adverse Effects -- Repeated Measures Methods for Testing Adverse Effects -- Benefit Risk Ratios -- Equivalence, Non-inferiority and Superiority Testing of Adverse Effects -- Part II The Analysis of Dependent Adverse Effects -- Independent and Dependent Adverse Effects. Categorical Predictors Assessed as Dependent Adverse Effects. Adverse Effect of the Dependent Type in Crossover Trial -- Confoundings and Interactions Assessed as Dependent Adverse Effects -- Subgroup Characteristics Assessed as Dependent Adverse Effects -- Random Effects Assessed as Dependent Adverse Effects -- Outliers Assessed as Dependent Adverse Effects -- Index.
520 $a The authors, as professors in statistics at various universities in Europe, are worrried about the poor quality of safety data analysis of clinical trials, despite its importance in drug development and pharmacovigilance. Clinical trials, not adequately addressing safety, are unethical. An effective approach for the purpose is to present summaries of prevalences. In order to estimate the probability, that the differences between treatment and control group did not occur merely by chance, a statistical test can be performed. This pretty crude method has recently be supplemented with better sensitive methodologies, based on machine learning clusters and networks, and multivariate analyses. Another important novelty with safety data analysis is the new insights into hypothesis testing, favoring the alternative hypotheses instead of the null hypotheses. Finally the issue of dependency is addressed. Adverse effects may be either dependent or independent of the main outcome. Dependent adverse effect are dependent not only on the treatment modalities, but also on the outcome of the trials. Random heterogeneities, outliers, confounders, interaction factors are common in clinical trials, and all of them can be considered kinds of adverse effects of the dependent type. Random regressions and analyses of variance, high dimensional clusterings, partial correlations, structural equations models, and other Bayesian methods are helpful for their analysis. The current edition was particularly written for medical and health professionals and students. It provides examples of modern analytic methods so far largely unused. All of the 16 chapters have two core characteristics, first they are for current usage, second they try and tell what readers need to know in order to understand the methods. Step by step analyses are given and self-assessment examples are supplied. Each chapter can be studied as a stand-alone.
650 0 $a Drugs $x Testing. $3 183737
650 0 $a Drugs $x Side effects. $3 375432
650 1 4 $a Biomedicine general. $3 273948
650 2 4 $a Statistics and Computing/Statistics Programs. $3 275710
700 1 $a Zwinderman, Aeilko H. $3 261385
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-3-030-05804-3
950 $a Biomedical and Life Sciences (Springer-11642)