All Stories

  1. Randomised clinical trials are experiments not surveys.
  2. A review of David Brunt's 1917 book on combining results of different studies.
  3. A step by step guide to analysing sets of n-of-1 trials using simple explanations.
  4. The analysis of continuous data from n-of-1 trials using paired cycles: a simple tutorial
  5. Statistical issues in a study of the effect of milk on growth of schoolchildren
  6. Conditions for success and margins of error: Estimation in clinical trials
  7. Heterogeneity in meta-analysis
  8. On the relevance of prognostic information for clinical trials: A theoretical quantification
  9. 1000 Patients are not Necessary for Balance in a Randomised Trial
  10. The design and analysis of COVID vaccine trials.
  11. Problems with the two-stage analysis of cross-over trials
  12. Ten simple rules for good research practice
  13. The statistical properties of RCTs and a proposal for shrinkage
  14. Using Historical Controls in Oncology
  15. The outstanding scientist, R.A. Fisher: his views on eugenics and race
  16. Cluster trials are a closer analogue to studies using historical controls than parallel group trials
  17. A scientific biography of John Nelder
  18. Treatment Effects in Multicenter Randomized Clinical Trials
  19. Modelling treatment main effects as random in network meta-analyses with many similar treatments
  20. Naive statistics lead to misunderstandings about personalised medicine
  21. Childhood asthma exacerbations and ADRB2 polymorphism: Caution is needed
  22. Evidence against precision medicine?
  23. The origin of the data that Student used to illustrate his t-test in his famous paper of 1908.
  24. Sample sizes needed to attain chosen power when planning groups of n-of-1 trials
  25. A partial if not impartial defence of P-values
  26. Statistical issues in first-in-human studies on BIA 10-2474: Neglected comparison of protocol against practice
  27. Variation in N-of-1 Trials
  28. Why the scope for personalizing medicine may be less than you think
  29. Progression-seeking bias and rational optimism in research and development
  30. Individual response to exercise training - a statistical perspective
  31. Pharmaceutical Industry, Statistics in: Including Two Examples
  32. Justice, Rawlsian Theory of
  33. Pharma industry productivity is not so great after all
  34. Meta-analysis of sequential trials
  35. Crossover Designs
  36. Statistics in Medicine
  37. Baseline Adjustment in Longitudinal Studies
  38. Caution needed in using Lee's checks for relative risks.
  39. Designing proof of concept trials for treatment of pain
  40. Paediatric legislation may be bad for children
  41. What does 'random effect' mean?
  42. Sources of variation in observed response in trials in pain
  43. Various varying variances
  44. Review of Bad Pharma
  45. Predicting patient recruitment
  46. Contribution to Bob O'Neil Festschrift
  47. Errors of conditional probability
  48. A reply to Chalmers and Dickersin
  49. A note on randomization
  50. Crossover design
  51. P-values explained
  52. Myths of randomisation
  53. When understood properly the data show that editors have a bias in favour of positive results
  54. Editors are biased against negative studies
  55. Tea for three
  56. It works in practice, but does it work in theory?
  57. Dealing with observations below the limit of quantitation
  58. Lecture at the 2011 clinical trials conference in Bristol
  59. Simplicity versus complexity in modelling
  60. Chapter 3 of the book Simplicity Complexity and Modelling
  61. Chapter 2 of Simplicity, Complexity and Modelling
  62. Model selection and other matters
  63. Chapter 1 of Simplicity, Complexity and Modelling
  64. Review of Fleiss, statistical methods for rates and proportions
  65. Francis Galton and regression to the mean
  66. SAS Macros for meta-analysis
  67. Randomisation does not cure all problems but it is still valuable
  68. Cross-over trials in infertility
  69. RA Fisher and significance
  70. PK modellers and statisticians should collaborate
  71. Design and Analysis of Cross-over Trials
  72. Understanding P-values
  73. Efficiency of two approaches to dynamic balancing in clinical trials
  74. Some remarks concerning meta-analysis
  75. Commentary on Rosemary' Baily's paper on dose escalation
  76. Authors' Rejoinder to Commentaries on ‘Measurement in clinical trials: A neglected issue for statisticians?’
  77. Measurement in Clinical Trials
  78. Comment on Robert et al
  79. Double counting in meta-analysis and related problems
  80. Invited comment on a paper by Ioannidis
  81. Correction
  82. Dawid's selection paradox
  83. Editorial/Letters
  84. Two trials illustrating points about randomisation
  85. A dram of data is worth a pint of pontification
  86. Faculty Opinions recommendation of Are flexible designs sound?
  87. When and how to use the t-test
  88. The history of the t-test
  89. Budesonide and Formoterol in Combination: an Incomplete Blocks Cross-over
  90. Authors' Reply
  91. A comment on an article by Andrew Gelman
  92. Statistical Issues
  93. The propensity score is problematic
  94. Multiple endpoints plus Bonferroni may gain power
  95. Safety first?
  96. Drawbacks to Noninteger Scoring for Ordered Categorical Data
  97. Faculty Opinions recommendation of Semiparametric analysis of case series data.
  98. Cross-over trials in Statistics in Medicine : the first ‘25’ years
  99. Sharp tongues and bitter pills
  100. Lord's paradox and ANCOVA
  101. Prior distributions for random effect meta-analysis
  102. Epigenetic analysis must allow for dependence of observations
  103. An Early “Atkins' Diet”: RA Fisher Analyses a Medical “Experiment”
  104. Faculty Opinions recommendation of Surrogate endpoints in clinical trials: definition and operational criteria.
  105. Faculty Opinions recommendation of A likelihood approach to meta-analysis with random effects.
  106. Medicine, Statistics in
  107. Rawlsian
  108. Statistics in Medicine
  109. Errors in understanding cross-over trials
  110. Bitter Pills and Puffed Trials
  111. Bernoulli Family
  112. Comment
  113. Sizing up the world
  114. Crossover designs
  115. Pharmaceutical Industry, Statistics In
  116. Baseline Adjustment in Longitudinal Studies
  117. Some comments on therapeutic equivalence
  118. Authors' Reply
  119. Modelling may save lives and money
  120. Controversies concerning randomization and additivity in clinical trials
  121. Bioequivalence for beginners
  122. Medicine, Statistics in
  123. Justice, Rawlsian Theory of
  124. Tribute to John Nelder on his 80th birthday
  125. The analysis of the AB/BA cross‐over trial in the medical literature
  126. Carry‐over in cross‐over trials in bioequivalence: theoretical concerns and empirical evidence
  127. Preface
  128. Chance, risk and health
  129. Circling the square
  130. Chapter 2 of Dicing with Death
  131. Trials of life
  132. Of dice and men
  133. Time's tables
  134. Sex and the single patient
  135. A hale view of pills
  136. Meta-analysis and related matters
  137. The things that bug us
  138. The empire of the sum
  139. The law is a ass
  140. Preface
  141. Permissions
  142. Dichotomising continuous outcomes is bad
  143. Patents, pharmaceuticals & statistics
  144. P-Values
  145. Crossover Design
  146. Examples of option values in drug development
  147. John Nelder: life and work
  148. Lost opportunities for statistics
  149. Caution is needed in applying nonparametric ANCOVA
  150. Replication probabilities of P-values are irrelevant
  151. A practical text on designing and analysing cross-over trials
  152. Pharma scientists should appear more often on publications
  153. The Unpleasant Placebo?
  154. Screening for breast cancer with mammography
  155. Problems in personalising medicine
  156. Controversies in bioequivalance
  157. The p-value and its critics
  158. Letters to the Editor
  159. Statistical Issues in Clinical Trials in Neurology
  160. Linear models versus meta-analysis in analysing multi-centre trials
  161. Consensus and Controversy in Pharmaceutical Statistics
  162. Letters to the editor
  163. The summary measures approach for clinical trials
  164. Screening mammography re-evaluated
  165. A Comment on Optimal Allocations for Bioequivalence Studies
  166. Preface
  167. Realistic models for carry-over
  168. Robust and realistic approaches to carry‐over
  169. Correspondence
  170. Some controversies in planning and analysing multi‐centre trials
  171. Individual bioequivalance is unnecessary
  172. Bayesian and frequentist approaches to the cross-over trial
  173. Uncertainty can be valuable in drug development
  174. Why you should not use the two-stage analysis of AB/BA cross-overs
  175. On wisdom after the event
  176. P100 Individualizing patient therapy
  177. 35 How to perform the two-stage analysis of cross-over trials if you can't be persuaded not to
  178. A violation of informed consent
  179. Pharmaceutical Project Prioritization
  180. How to rank drug development projects
  181. A Comment on Interim Analyses in Crossover Trials
  182. Controversies in clinical trials
  183. In defence of analysis of covariance: A reply to Chambless and Roeback
  184. Use baseline covariates rather than testing them
  185. Cushny, Peebles & Student
  186. Randomisation in clinical trials
  187. A Bayesian paradox of confirmation
  188. Regression toward the mean in 2 × 2 crossover designs with baseline measurements
  189. Suspended judgment n-of-1 trials
  190. Baseline distribution and conditional size
  191. Letters to the editor
  192. A Popperian view of clinical trials
  193. Competence, control, confirmation and refutation
  194. Review of Howson and Urbach
  195. Regression is not always to the mode
  196. Covariance analysis in generalized linear measurement error models
  197. Combining Outcome Measures: Statistical Power Is Irrelevant
  198. Testing for covariate imbalance does not deal with it
  199. Analysis of an epidemic of Q Fever
  200. Sober view of AIDS
  201. Estimating regression to the mean