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