This paper discusses the statistical principles, methods, and software programs used to calculate sample size. In addition, it reviews the practical challenges faced in calculating sample size. We show that because of such challenges, statistical calculations often do not provide us with a clear-cut number for the study sample size; rather they suggest a range of reasonable numbers. The paper a...

Network meta-analysis is becoming more popular as a way to compare multiple treatments simultaneously. Here, we develop a new estimation method for fitting models for network meta-analysis with random inconsistency effects. This method is an extension of the procedure originally proposed by DerSimonian and Laird. Our methodology allows for inconsistency within the network. The proposed procedur...

It has been demonstrated recently that the empirical significance levels of the J-type tests introduced by Kelejian (2008) can be controlled in many cases by the use of a bootstrap to construct a reference distribution. When the spatial parameter estimates lie outside the invertibility region constructing bootstrap samples is problematic, however, and the present paper explores how far this pra...

Statistical sciences have recently made advancements that allow improved precision or reduced sample size in clinical research studies. Herein, we review 4 of the more promising: (1) improvements in approaches for dose selection trials, (2) approaches for sample size adjustment, (3) selection of study end point and associated statistical methods, and (4) frequentist versus Bayesian statistical ...

A PhRMA Working Group on adaptive clinical trial designs has been formed to investigate and facilitate opportunities for wider acceptance and usage of adaptive designs and related methodologies. A White Paper summarizing the findings of the group is in preparation; this article is an Executive Summary for that full White Paper, and summarizes the findings and recommendations of the group. Logis...

S size is a crucial component of research design. More often researchers want sample size to be justified on non statistical grounds. For example, a researcher may say that I could get only these many cases in the specified time period so as a statistician do something to make the study valid in spite of whatever sample size I have used. Similarly, financial constraint is sometimes cited an exc...

Two-stage trial designs provide the flexibility to stop early for efficacy or futility and are popular because they have a smaller sample size on average than a traditional trial has with the same type I and II error rates. This makes them financially attractive but also has the ethical benefit of reducing, in the long run, the number of patients who are given ineffective treatments. Designs th...

Randomised controlled trials (RCTs) are generally regarded as the gold standard for evaluating health care interventions. The level of uncertainty around a trial's estimate of effect is, however, frequently linked to how successful the trial has been in recruiting and retaining participants. As recruitment is often slower or more difficult than expected, with many trials failing to reach their ...

A method of computer simulation is applied to the investigation of problems connected with the genetic analysis of continuously variable behavioral characters in human populations. The efficiency with which various components of genetic and environmental variation can be detected is related to sample size. It is found that a convincing partition of the genetic variance into its additive and non...

Adaptive clinical trials are becoming very popular because of their flexibility in allowing mid-stream changes of sample size, endpoints, populations, etc. At the same time, they have been regarded with mistrust because they can produce bizarre results in very extreme settings. Understanding the advantages and disadvantages of these rapidly developing methods is a must. This paper reviews flexi...