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Sample Size Tables for Clinical Studies
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Main description:

This book provides statisticians and researchers with the statistical tools – equations, formulae and numerical tables – to design and plan clinical studies and carry out accurate, reliable and reproducible analysis of the data so obtained. There is no way around this as incorrect procedure in clinical studies means that the researcher′s paper will not be accepted by a peer–reviewed journal. Planning and analysing clinical studies is a very complicated business and this book provides indispensible factual information.


Back cover:

This book provides statisticians and researchers with the statistical tools – equations, formulae and numerical tables – to design and plan clinical studies and carry out accurate, reliable and reproducible analysis of the data so obtained. There is no way around this as incorrect procedure in clinical studies means that the researcher′s paper will not be accepted by a peer–reviewed journal. Planning and analysing clinical studies is a very complicated business and this book provides indispensible factual information.


Contents:

Preface, viii.

1 Basic design considerations, 1


2 Distributions and confidence intervals, 14


Table 2.1 The Normal distribution functionaprobability that aNormally distributed variable is less than z, 27


Table 2.2 Percentage points of the Normal distribution for a and1 – ß, 28


Table 2.3 Values of ?(a, ß) = (z1–a/2 + z1–ß)2, 28


Table 2.4 The t–distribution, 29


3 Comparing two independent groups for binary data,30


Table 3.1 Sample size for the comparison of two proportions,38


Table 3.2 Sample size for the comparison of two proportionsusing the odds ratio (OR), 40


4 Comparing two independent groups for ordered categoricaldata, 42


5 Comparing two independent groups for continuous data,47


Table 5.1 Sample sizes for the two sample t–test with two–sideda = 0.05, 54


Table 5.2 Sample sizes for the two sample t–test with unequalvariances, 55


Table 5.3 Sample sizes for the one sample t–test with two–sideda = 0.05, 57


6 Cluster designs, repeated measures data and more than twogroups, 58


Table 6.1 Multiplying factor for repeated measures designs,66


7 Comparing paired groups for binary, ordered categorical andcontinuous outcomes, 67


Table 7.1 Sample sizes for paired binary data, 80


Table 7.2 Sample sizes for paired continuous data with two–sideda = 0.05, 81


8 Comparing survival curves, 82


Table 8.1 Number of critical events for comparison of survivalrates (Logrank test), 95


Table 8.2 Number of subjects for comparison of survival rates(Logrank test), 97


Table 8.3 Number of critical events for comparison of twoexponential survival distributions with two–sided a = 0.05, 99


9 Equivalence, 100


Table 9.1 Sample sizes for bioequivalence studiesadifferencebetween two means or ratio of two means, 115


Table 9.2 Sample sizes for testing the equivalence of two means,116


Table 9.3 Sample sizes for testing the equivalence of twoproportions, 118


10 Confidence intervals, 120


Table 10.1 Sample sizes required to observe a given confidenceinterval width for a given proportion in a sample from a largepopulation, 134


Table 10.2 Sample sizes required to observe a given confidenceinterval width for the difference between twoproportionsaindependent groups, 135


Table 10.3 Sample sizes required to observe a proportionateconfidence interval width for the difference between two groupsexpressed via the odds ratio (OR), 136


Table 10.4 Sample sizes required to observe a given confidenceinterval width for the difference between two proportions frompaired or matched groups, 137


Table 10.5 Sample sizes required to observe a given confidenceinterval width to estimate a single mean or the difference betweentwo means for independent or matched groups, 139


11 Post–marketing surveillance, 140


Table 11.1 Sample sizes required to observe a total of a adversereactions with a given probability 1 – ß and anticipatedincidence ?, 147


Table 11.2 Sample sizes required for detection of a specificadverse reaction with background incidence, ?0, known, 148


Table 11.3 Sample sizes required for detection of a specificadverse reaction with background incidence unknown, 149


Table 11.4 Number of cases to be observed in a case–controlstudy, 150


12 The correlation coefficient, 151


Table 12.1 Sample sizes for detecting a statisticallysignificant correlation coefficient, 155


13 Reference intervals and receiver operating curves,156


Table 13.1 Sample sizes in order to obtain a required referenceintervalaNormal distribution, 167


Table 13.2 Sample sizes in order to obtain a required referenceintervalanon–Normal distribution, 168


Table 13.3 Sample sizes required to observe a given sensitivityand specificity in diagnostic accuracy studiesasingle sample,169


Table 13.4 Sample sizes required to observe a given sensitivityand specificity in diagnostic accuracy studiesatwo sample unpaireddesign, 171


Table 13.5 Sample sizes required to observe a given sensitivityand specificity in diagnostic accuracy studiesatwo sample matchedpaired design, 173


Table 13.6 Sample sizes required to observe a given confidenceinterval width for receiver operating curves (ROC), 175


14 Observer agreement studies, 177


Table 14.1 Sample sizes required to observe a given confidenceinterval to estimate the proportion of disagreements between twoobservers, 187


Table 14.2 Sample sizes required to observe a given confidenceinterval to estimate the within observer variation, 188


Table 14.3 Sample sizes required to observe a given confidenceinterval to minimise the number of subjects required to achieve thedesired precision in the probability of their disagreement, TDis,189


Table 14.4 Sample sizes required to observe a given confidenceinterval width for inter–observer agreement using Cohen′s Kappa?,190


Table 14.5 Sample sizes required to observe a given intra–classcorrelation using confidence interval approach, 191


Table 14.6 Sample sizes required to observe a given intra–classcorrelation using hypothesis testing approach with two–sided a =0.05, 192


15 Dose finding studies, 193


16 Phase II trials, 205


Table 16.1 Fleming A Hern single–stage Phase IIdesign, 223


Table 16.2 Gehan two–stage Phase II designaStage 1, 224


Table 16.3 Gehan two–stage Phase II designaStage 2, 225


Table 16.4 Simon Optimal and Minimax designs, 226


Table 16.5 Bayesian single threshold design (STD), 227


Table 16.6 Bayesian dual threshold design (DTD), 228


Table 16.7 Case and Morgan design (EDA) with a = 0.05, 229


Table 16.8 Case and Morgan design (ETSL) with a = 0.05, 230


Table 16.9 Simon, Wittes and Ellenberg design, 231


Table 16.10 Bryant and Day design, 233


17 Sample size software , 235


Cumulative references, 237


Index, 247


PRODUCT DETAILS

ISBN-13: 9781444300727
Publisher: John Wiley & Sons Ltd (Wiley–Blackwell)
Publication date: November, 2008
Pages: 264
Dimensions: 195.00 x 254.00 x 20.14

Subcategories: Diseases and Disorders, General Issues, Pharmacology

MEET THE AUTHOR



David Machin, Children s Cancer and LeukaemiaGroup, University of Leicester, UK; Division of Clinical Trials andEpidemiological Sciences, National Cancer Centre, Singapore;Medical Statistics Unit, School of Health and Related Sciences,University of Sheffield, UK


Michael J. Campbell, Medical Statistics Unit, School ofHealth and Related Sciences, University of Sheffield, UK


Say Beng Tan, Singapore Clinical Research Institute,Singapore; Duke NUS Graduate Medical School,Singapore


Sze Huey Tan, Division of Clinical Trials andEpidemiological Sciences, National Cancer Centre, Singapore