All Stories

  1. An early 20th century handbook on ‘meta-analysis’: David Brunt’s The Combination of Observations
  2. A step by step guide to analysing sets of n-of-1 trials using simple explanations.
  3. Statistical issues in a study of the effect of milk on growth of schoolchildren
  4. Conditions for success and margins of error: Estimation in clinical trials
  5. Heterogeneity in meta-analysis
  6. On the relevance of prognostic information for clinical trials: A theoretical quantification
  7. 1000 Patients are not Necessary for Balance in a Randomised Trial
  8. The design and analysis of COVID vaccine trials.
  9. Problems with the two-stage analysis of cross-over trials
  10. Using Historical Controls in Oncology
  11. Cluster trials are a closer analogue to studies using historical controls than parallel group trials
  12. A scientific biography of John Nelder
  13. Modelling treatment main effects as random in network meta-analyses with many similar treatments
  14. Naive statistics lead to misunderstandings about personalised medicine
  15. Childhood asthma exacerbations and ADRB2 polymorphism: Caution is needed
  16. Evidence against precision medicine?
  17. The origin of the data that Student used to illustrate his t-test in his famous paper of 1908.
  18. Sample sizes needed to attain chosen power when planning groups of n-of-1 trials
  19. A partial if not impartial defence of P-values
  20. Statistical issues in first-in-human studies on BIA 10-2474: Neglected comparison of protocol against practice
  21. Variation in N-of-1 Trials
  22. Why the scope for personalizing medicine may be less than you think
  23. Progression-seeking bias and rational optimism in research and development
  24. Individual response to exercise training - a statistical perspective
  25. Pharmaceutical Industry, Statistics in: Including Two Examples
  26. Justice, Rawlsian Theory of
  27. Pharma industry productivity is not so great after all
  28. Meta-analysis of sequential trials
  29. Crossover Designs
  30. Statistics in Medicine
  31. Baseline Adjustment in Longitudinal Studies
  32. Caution needed in using Lee's checks for relative risks.
  33. Designing proof of concept trials for treatment of pain
  34. Paediatric legislation may be bad for children
  35. What does 'random effect' mean?
  36. Sources of variation in observed response in trials in pain
  37. Various varying variances
  38. Review of Bad Pharma
  39. Predicting patient recruitment
  40. Contribution to Bob O'Neil Festschrift
  41. Errors of conditional probability
  42. A reply to Chalmers and Dickersin
  43. A note on randomization
  44. Crossover design
  45. P-values explained
  46. Myths of randomisation
  47. When understood properly the data show that editors have a bias in favour of positive results
  48. Editors are biased against negative studies
  49. Tea for three
  50. It works in practice, but does it work in theory?
  51. Dealing with observations below the limit of quantitation
  52. Lecture at the 2011 clinical trials conference in Bristol
  53. Simplicity versus complexity in modelling
  54. Chapter 3 of the book Simplicity Complexity and Modelling
  55. Chapter 2 of Simplicity, Complexity and Modelling
  56. Model selection and other matters
  57. Chapter 1 of Simplicity, Complexity and Modelling
  58. Review of Fleiss, statistical methods for rates and proportions
  59. Francis Galton and regression to the mean
  60. SAS Macros for meta-analysis
  61. Randomisation does not cure all problems but it is still valuable
  62. Cross-over trials in infertility
  63. RA Fisher and significance
  64. PK modellers and statisticians should collaborate
  65. Design and Analysis of Cross-over Trials
  66. Understanding P-values
  67. Efficiency of two approaches to dynamic balancing in clinical trials
  68. Some remarks concerning meta-analysis
  69. Commentary on Rosemary' Baily's paper on dose escalation
  70. Authors' Rejoinder to Commentaries on ‘Measurement in clinical trials: A neglected issue for statisticians?’
  71. Measurement in Clinical Trials
  72. Comment on Robert et al
  73. Double counting in meta-analysis and related problems
  74. Invited comment on a paper by Ioannidis
  75. Correction
  76. Dawid's selection paradox
  77. Editorial/Letters
  78. Two trials illustrating points about randomisation
  79. A dram of data is worth a pint of pontification
  80. Faculty Opinions recommendation of Are flexible designs sound?
  81. When and how to use the t-test
  82. The history of the t-test
  83. Budesonide and Formoterol in Combination: an Incomplete Blocks Cross-over
  84. Authors' Reply
  85. A comment on an article by Andrew Gelman
  86. Statistical Issues
  87. The propensity score is problematic
  88. Multiple endpoints plus Bonferroni may gain power
  89. Safety first?
  90. Drawbacks to Noninteger Scoring for Ordered Categorical Data
  91. Faculty Opinions recommendation of Semiparametric analysis of case series data.
  92. Cross-over trials in Statistics in Medicine : the first ‘25’ years
  93. Sharp tongues and bitter pills
  94. Lord's paradox and ANCOVA
  95. Prior distributions for random effect meta-analysis
  96. Epigenetic analysis must allow for dependence of observations
  97. An Early “Atkins' Diet”: RA Fisher Analyses a Medical “Experiment”
  98. Faculty Opinions recommendation of Surrogate endpoints in clinical trials: definition and operational criteria.
  99. Faculty Opinions recommendation of A likelihood approach to meta-analysis with random effects.
  100. Medicine, Statistics in
  101. Rawlsian
  102. Statistics in Medicine
  103. Errors in understanding cross-over trials
  104. Bitter Pills and Puffed Trials
  105. Bernoulli Family
  106. Comment
  107. Sizing up the world
  108. Crossover designs
  109. Pharmaceutical Industry, Statistics In
  110. Baseline Adjustment in Longitudinal Studies
  111. Some comments on therapeutic equivalence
  112. Authors' Reply
  113. Modelling may save lives and money
  114. Controversies concerning randomization and additivity in clinical trials
  115. Bioequivalence for beginners
  116. Medicine, Statistics in
  117. Justice, Rawlsian Theory of
  118. Tribute to John Nelder on his 80th birthday
  119. The analysis of the AB/BA cross‐over trial in the medical literature
  120. Carry‐over in cross‐over trials in bioequivalence: theoretical concerns and empirical evidence
  121. Preface
  122. Chance, risk and health
  123. Circling the square
  124. Chapter 2 of Dicing with Death
  125. Trials of life
  126. Of dice and men
  127. Time's tables
  128. Sex and the single patient
  129. A hale view of pills
  130. Meta-analysis and related matters
  131. The things that bug us
  132. The empire of the sum
  133. The law is a ass
  134. Preface
  135. Permissions
  136. Dichotomising continuous outcomes is bad
  137. Patents, pharmaceuticals & statistics
  138. P-Values
  139. Crossover Design
  140. Examples of option values in drug development
  141. John Nelder: life and work
  142. Lost opportunities for statistics
  143. Caution is needed in applying nonparametric ANCOVA
  144. Replication probabilities of P-values are irrelevant
  145. A practical text on designing and analysing cross-over trials
  146. Pharma scientists should appear more often on publications
  147. The Unpleasant Placebo?
  148. Screening for breast cancer with mammography
  149. Problems in personalising medicine
  150. Controversies in bioequivalance
  151. The p-value and its critics
  152. Letters to the Editor
  153. Statistical Issues in Clinical Trials in Neurology
  154. Linear models versus meta-analysis in analysing multi-centre trials
  155. Consensus and Controversy in Pharmaceutical Statistics
  156. Letters to the editor
  157. The summary measures approach for clinical trials
  158. Screening mammography re-evaluated
  159. A Comment on Optimal Allocations for Bioequivalence Studies
  160. Preface
  161. Realistic models for carry-over
  162. Robust and realistic approaches to carry‐over
  163. Correspondence
  164. Some controversies in planning and analysing multi‐centre trials
  165. Individual bioequivalance is unnecessary
  166. Bayesian and frequentist approaches to the cross-over trial
  167. Uncertainty can be valuable in drug development
  168. Why you should not use the two-stage analysis of AB/BA cross-overs
  169. On wisdom after the event
  170. P100 Individualizing patient therapy
  171. 35 How to perform the two-stage analysis of cross-over trials if you can't be persuaded not to
  172. A violation of informed consent
  173. Pharmaceutical Project Prioritization
  174. How to rank drug development projects
  175. A Comment on Interim Analyses in Crossover Trials
  176. Controversies in clinical trials
  177. In defence of analysis of covariance: A reply to Chambless and Roeback
  178. Use baseline covariates rather than testing them
  179. Cushny, Peebles & Student
  180. Randomisation in clinical trials
  181. A Bayesian paradox of confirmation
  182. Regression toward the mean in 2 × 2 crossover designs with baseline measurements
  183. Suspended judgment n-of-1 trials
  184. Baseline distribution and conditional size
  185. Letters to the editor
  186. A Popperian view of clinical trials
  187. Competence, control, confirmation and refutation
  188. Review of Howson and Urbach
  189. Regression is not always to the mode
  190. Covariance analysis in generalized linear measurement error models
  191. Combining Outcome Measures: Statistical Power Is Irrelevant
  192. Testing for covariate imbalance does not deal with it
  193. Analysis of an epidemic of Q Fever
  194. Sober view of AIDS
  195. Estimating regression to the mean