By N. Balakrishnan, Nandini Kannan, H. N. Nagaraja
"S. Panchapakesan has made major contributions to rating and choice and has released in lots of different components of statistics, together with order facts, reliability thought, stochastic inequalities, and inference. Written in his honor, the twenty invited articles during this quantity mirror fresh advances in those fields and shape a tribute to Panchapakesan's impression and influence on those components. that includes conception, tools, purposes, and large bibliographies with specified emphasis on contemporary literature, this entire reference paintings will serve researchers, practitioners, and graduate scholars within the statistical and utilized arithmetic groups.
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Extra info for Advances in Ranking and Selection, Multiple Comparisons, and Reliability
The decision about which, when and how measurements are to be made needs to be taken before the trial commences. The alternative is potential chaos. Attention clearly needs to be given to training clinicians and others on the measuring instruments to be used; this is particularly important in multi-centre trials. Results from studies based on poorly standardised procedures that use ambiguous definitions or conducted by insufficiently trained staff, can lead to both loss of power and bias in the estimate of treatment effect.
There are, however, other more complex randomisation schemes designed to achieve various objectives. We begin, though, with a few comments about the simple ‘coin tossing’ type of randomisation process. (Although we shall concentrate largely on trials in which the unit of randomisation is the individual patient, it is important to note that there are trials in which, for example, complete families are randomised to the various treatments to be compared. 1. 21 Simple Randomisation For a randomised trial with two treatments, A and B, the basic concept of tossing a coin over and over again and allocating a patient to A if a head appears and B if the coin shows tails, is quite reasonable, but is rarely if ever used in practice.
But, in the recent past at least, such advice has often not been heeded and the literature is dotted with accounts of inconsequential trials. Freiman et al. , trials in which the observed differences between the proposed and control treatments were not large enough to satisfy a specified ‘significance’ level (the risk of a type I error), and the results were declared to be ‘not statistically significant’. Analysis of these clinical studies indicated that the investigators often worked with numbers of enrolled patients too small to offer a reasonable chance of avoiding the opposing mistake, a type II error.