Sample Size Tables for Clinical Studies, 3rd EditionISBN: 9781405146500
264 pages
December 2008, BMJ Books

Description
Please go to http://booksupport.wiley.com and enter 9781405146500 to easily download the supporting materials.
Table of Contents
1 Basic design considerations, 1
2 Distributions and confidence intervals, 14
Table 2.1 The Normal distribution functionaprobability that a Normally distributed variable is less than z, 27
Table 2.2 Percentage points of the Normal distribution for a and 1  ß, 28
Table 2.3 Values of ?(a, ß) = (z1a/2 + z1ß)2, 28
Table 2.4 The tdistribution, 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 proportions using the odds ratio (OR), 40
4 Comparing two independent groups for ordered categorical data, 42
5 Comparing two independent groups for continuous data, 47
Table 5.1 Sample sizes for the two sample ttest with twosided a = 0.05, 54
Table 5.2 Sample sizes for the two sample ttest with unequal variances, 55
Table 5.3 Sample sizes for the one sample ttest with twosided a = 0.05, 57
6 Cluster designs, repeated measures data and more than two groups, 58
Table 6.1 Multiplying factor for repeated measures designs, 66
7 Comparing paired groups for binary, ordered categorical and continuous outcomes, 67
Table 7.1 Sample sizes for paired binary data, 80
Table 7.2 Sample sizes for paired continuous data with twosided a = 0.05, 81
8 Comparing survival curves, 82
Table 8.1 Number of critical events for comparison of survival rates (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 two exponential survival distributions with twosided a = 0.05, 99
9 Equivalence, 100
Table 9.1 Sample sizes for bioequivalence studiesadifference between 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 two proportions, 118
10 Confidence intervals, 120
Table 10.1 Sample sizes required to observe a given confidence interval width for a given proportion in a sample from a large population, 134
Table 10.2 Sample sizes required to observe a given confidence interval width for the difference between two proportionsaindependent groups, 135
Table 10.3 Sample sizes required to observe a proportionate confidence interval width for the difference between two groups expressed via the odds ratio (OR), 136
Table 10.4 Sample sizes required to observe a given confidence interval width for the difference between two proportions from paired or matched groups, 137
Table 10.5 Sample sizes required to observe a given confidence interval width to estimate a single mean or the difference between two means for independent or matched groups, 139
11 Postmarketing surveillance, 140
Table 11.1 Sample sizes required to observe a total of a adverse reactions with a given probability 1  ß and anticipated incidence ?, 147
Table 11.2 Sample sizes required for detection of a specific adverse reaction with background incidence, ?0, known, 148
Table 11.3 Sample sizes required for detection of a specific adverse reaction with background incidence unknown, 149
Table 11.4 Number of cases to be observed in a casecontrol study, 150
12 The correlation coefficient, 151
Table 12.1 Sample sizes for detecting a statistically significant correlation coefficient, 155
13 Reference intervals and receiver operating curves, 156
Table 13.1 Sample sizes in order to obtain a required reference intervalaNormal distribution, 167
Table 13.2 Sample sizes in order to obtain a required reference intervalanonNormal distribution, 168
Table 13.3 Sample sizes required to observe a given sensitivity and specificity in diagnostic accuracy studiesasingle sample, 169
Table 13.4 Sample sizes required to observe a given sensitivity and specificity in diagnostic accuracy studiesatwo sample unpaired design, 171
Table 13.5 Sample sizes required to observe a given sensitivity and specificity in diagnostic accuracy studiesatwo sample matched paired design, 173
Table 13.6 Sample sizes required to observe a given confidence interval width for receiver operating curves (ROC), 175
14 Observer agreement studies, 177
Table 14.1 Sample sizes required to observe a given confidence interval to estimate the proportion of disagreements between two observers, 187
Table 14.2 Sample sizes required to observe a given confidence interval to estimate the within observer variation, 188
Table 14.3 Sample sizes required to observe a given confidence interval to minimise the number of subjects required to achieve the desired precision in the probability of their disagreement, TDis, 189
Table 14.4 Sample sizes required to observe a given confidence interval width for interobserver agreement using Cohen's Kappa?, 190
Table 14.5 Sample sizes required to observe a given intraclass correlation using confidence interval approach, 191
Table 14.6 Sample sizes required to observe a given intraclass correlation using hypothesis testing approach with twosided a = 0.05, 192
15 Dose finding studies, 193
16 Phase II trials, 205
Table 16.1 Fleming–A’Hern singlestage Phase II design, 223
Table 16.2 Gehan twostage Phase II designaStage 1, 224
Table 16.3 Gehan twostage 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
Author Information
David Machin, Children’s Cancer and Leukaemia
Group, University of Leicester, UK; Division of Clinical Trials and
Epidemiological 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 of
Health 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 and Epidemiological Sciences, National Cancer Centre, Singapore
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