Format:
Online-Ressource (XXXV, 743p. 186 illus, digital)
Edition:
5th ed. 2012
ISBN:
9789400728639
Series Statement:
SpringerLink
Content:
Thanks to the omnipresent computer, current statistics can include data files of many thousands of values, and can perform any exploratory analysis in less than seconds. This development, however fascinating, generally does not lead to simple results. We should not forget that clinical studies are, mostly, for confirming prior hypotheses based on sound arguments, and the simplest tests provide the best power and are adequate for such studies. In the past few years the authors of this 5th edition, as teachers and research supervisors in academic and top-clinical facilities, have been able to closely observe the latest developments in the field of clinical data analysis, and they have been able to assess their performance. In this 5th edition the 47 chapters of the previous edition have been maintained and upgraded according to the current state of the art, and 20 novel chapters have been added after strict selection of the most valuable and promising novel methods. The novel methods are explained using practical examples and step-by-step analyses readily accessible for non-mathematicians. All of the novel chapters have been internationally published by the authors in peer-reviewed journal, including the American Journal of Therapeutics, the European Journal of Clinical Investigation, The International journal of Clinical Pharmacology and therapeutics, and other journals, and permission is granted by all of them to use this material in the current book. We should add that the authors are well-qualified in their fields of knowledge. Professor Zwinderman is president-elect of the International Society of Biostatistics, and Professor Cleophas is past-president of the American College of Angiology. From their expertise they should be able to make adequate selections of modern methods for clinical data analysis for the benefit of physicians, students, and investigators. The authors, although from a different discipline, one clinician and one statistician, have been working and publishing together for over 10 years, and their research of statistical methodology can be characterized as a continued effort to demonstrate that statistics is not mathematics but rather a discipline at the interface of biology and mathematics. They firmly believe that any reader can benefit from this clinical approach to statistical data analysis
Note:
Includes bibliographical references and index
,
Hypotheses, Data, StratificationThe Analysis of Efficacy DataThe Analysis of Safety DataLog Likelihood Ratio Tests for Safety Data AnalysisEquivalence TestingStatistical Power and Sample SizeInterim AnalysesControlling the Risk of False Positive Clinical TrialsMultiple Statistical InferencesThe Interpretation of the p-ValuesResearch Data Closer to Expectation than Compatible with Random SamplingStatistical Tables for Testing Data Closer to Expectation than Compatible with Random SamplingData Dispersion IssuesLinear Regression, Basic ApproachLinear Regression for Assessing Precision, Confounding, Interaction, Basic ApproachCurvilinear RegressionLogistic and Cox Regression, Markov Models, Laplace TransformationsRegression Modeling for Improved PrecisionPost-hoc Analyses in Clinical Trials, A Case for Logistic Regression AnalysisMultistage RegressionCategorical DataMissing DataPoisson RegressionMore on Non Linear Relationships, SplinesMultivariate AnalysisBhattacharya ModelingTrend-TestingConfoundingPropensity Score MatchingInteractionTime-Dependent Factor AnalysisMeta-analysis, Basic ApproachMeta-analysis, Review and Update of MethodologiesMeta-regressionCrossover Studies with Continuous VariablesCrossover Studies with Binary ResponsesCross-Over Trials Should Not Be Used to Test Treatments with Different Chemical ClassQuality-Of-Life Assessments in Clinical TrialsItem Response ModelingStatistical Analysis of Genetic DataRelationship Among Statistical DistributionsTesting Clinical Trials for RandomnessClinical Trials Do Not Use Random Samples AnymoreClinical Data Where Variability Is More Important Than AveragesTesting ReproducibilityValidating Qualitative Diagnostic TestsUncertainty of Qualitative Diagnostic TestsMeta-Analysis of Qualitative Diagnostic Testsc-Statistic Versus Logistic Regression for Assessing the Performance of Qualitative Diagnostic AccuracyValidating Quantitative Diagnostic TestsSummary of Validation Procedures for Diagnostic TestsValidating Surrogate Endpoints of Clinical TrialsBinary PartitioningMethods for Repeated Measures AnalysisMixed Linear Models for Repeated MeasuresAdvanced Analysis of Variance, Random Effects and Mixed Effects ModelsMonte Carlo Methods for Data AnalysisArtificial IntelligenceFuzzy LogicPhysicians' Daily Life and the Scientific MethodIncident Analysis and the Scientific MethodClinical Trials: Superiority-TestingNoninferiority TestingTime SeriesOdds Ratios and Multiple Regression Models, Why and How to Use ThemStatistics Is No "Bloodless" AlgebraBias Due to Conflicts of Interests, Some Guidelines.
Additional Edition:
ISBN 9789400728622
Additional Edition:
Buchausg. u.d.T. Cleophas, Ton J., 1947 - Statistics applied to clinical studies Dordrecht : Springer, 2012 ISBN 9789400728622
Language:
English
Subjects:
Psychology
,
Medicine
DOI:
10.1007/978-94-007-2863-9
URL:
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