Randomisation models and efficiency in experimental design

The study of the topic of randomisation models in the field of experimental design, was initiated by R.A, Fisher. Many of his contributions to this topic and to the general subject of experimental design are included in his book "The Design of Experiments". The study of efficiencies of experimental designs was first performed by F. Yates, who is acknowledged as the originator of many of the now standard complex designs. This thesis deals with these two topics, when related to classes of incomplete block designs. Chapter I surveys the historical development of randomisation. Special attention is given to studying the development of suitable alternatives to permutation testing, an exact method of hypothesis testing available when a randomisation model has been assumed. This chapter is mainly historical in content. The second chapter contains the randomisation analysis of a balanced incomplete block design with double grouping, a design originated by Robinson (1966). The efficiency of this design is then compared to some standard designs. This chapter is an extension of a paper prepared by Folks and Kempthorne (1960), which deals with the randomisation analysis and resulting efficiencies of a class of incomplete block designs. Graybill and Seshadri (1960) have shown that under the normal model assumptions the combined estimates of treatment contrasts in a balanced incomplete block design are unbiased. This estimate is a weighted estimate of treatment differences based on both inter—block and intra—block information. Chapter III is an extension of the above, to the set of balanced incomplete block designs under the randomisation model. A refinement in the method of proving that the estimate was unbiased, was suggested by my supervisor Mr. J. Robinson. The final chapter discusses the major studies which have been performed in developing suitable methods of hypothesis testing for randomisation models. In particular I have revised the study performed by Ogawa (1963), which shows that the usual F-test based on normality is a suitable approximation to the variance ratio test criterion obtained in a randomised balanced incomplete block design under the Neyman model. Ogawa‘s result is obtained by a more elegant and less stringent approach, using a technique developed by Kumar Mitra (1960)

Progesterone for the prevention of preterm birth in twin pregnancy (STOPPIT) : a randomized, double-blind, placebo-controlled study and meta-analysis EDITORIAL COMMENT

Women with twin pregnancy are at high risk of spontaneous preterm delivery. Three large randomized trials have shown that progesterone reduces the rate of preterm delivery in high-risk singleton pregnancies, although evidence of significant reduction in perinatal mortality or clear neonatal benefit in singleton women is lacking. The STOPPIT study was a randomized, double-blind, placebo-controlled trial designed to evaluate the potential benefit of progesterone for prevention of preterm birth in women with twin pregnancy. Between 2004 and 2008, 500 women with twin pregnancy were enrolled from 9 antenatal clinics at hospitals in the United Kingdom. At 24 weeks of gestation, the study subjects were randomized to either 90 mg of vaginal progesterone gel (n = 250) or placebo gel (n = 250) daily for 10 weeks. The primary study outcome was delivery or intrauterine death before 34 weeks of gestation. Analysis was performed according to intention to treat. The investigators also performed a meta-analysis of all published and unpublished studies in which women with twin pregnancy were randomly allocated to treatment with a progesterone (including progesterone). No significant difference was found between the 2 groups in the combined proportion of twin pregnancies that resulted in intrauterine death or delivery before 34 weeks (24.7% or 61/247 in the progesterone group vs. 19.4% or 48/247 in the placebo group; odds ratio, 1.36; 95% confidence interval, 0.89-2.09; P = 0.16). The meta-analysis, which included pooled data from 2 studies fulfilling inclusion criteria and data from the present study, confirmed that progesterone does not reduce the risk of early preterm birth or intrauterine death in twin pregnancies (pooled odds ratio, 1.16; 95% confidence interval, 0.89-1.51). No difference between the 2 groups was found in the rate of adverse events. These findings are consistent with previous studies showing that progestogens do not prevent preterm delivery in women with twin pregnancy