Background A pilot study can be an important step in the assessment of an intervention by providing information to design the future definitive trial. Pilot studies can be used to estimate the recruitment and retention rates and population variance and to provide preliminary evidence of efficacy potential. However, estimation is poor because pilot studies are small, so sensitivity analyses for ...

Two-stage designs are commonly used for Phase II trials. Optimal two-stage designs have the lowest expected sample size for a specific treatment effect, for example, the null value, but can perform poorly if the true treatment effect differs. Here we introduce a design for continuous treatment responses that minimizes the maximum expected sample size across all possible treatment effects. The p...

An approach to sample size planning for multiple regression is presented that emphasizes accuracy in parameter estimation (AIPE). The AIPE approach yields precise estimates of population parameters by providing necessary sample sizes in order for the likely widths of confidence intervals to be sufficiently narrow. One AIPE method yields a sample size such that the expected width of the confiden...

Multiple comparisons are commonly made in epidemiologic and genetic research. How to appropriately adjust for multiple comparisons remains a controversial issue. This note demonstrates, however, that large increases in the number of comparisons has a limited effect on the sample size required to maintain an experimentwise alpha-level. In particular, the relative sample size required increases o...

Background The evaluation of treatments for rare diseases presents a number of challenges for trial practitioners, regulators and policy makers. Small sample sizes mean that ‘standard’ approaches to trial design and analysis may not be appropriate and alternatives such as Bayesian trial designs have been recommended [Lilford et al 1995]. However, little is known about the design and analysis ap...

Using Tukey-Kramer versus the ANOVA F-test as the omnibus test of the Hayter-Fisher procedure for comparing all pairs of normally distributed means, when sample sizes are unequal, is investigated. Simulation results suggest that using Tukey-Kramer leads to as much or more any-pairs power compared to using the F-test for certain patterns of mean differences, and equivalent per-pair and all-pairs...

In clinical trials, the statistical concepts of significance and power are used in the determination of sample size for trials. The trialist must provide an estimate of standard deviation and a hypothetical population difference to be detected. This must be modified to deal with the designs encountered in guideline research. These are cluster randomized trials, because the patients of a single ...

Studies involving two methods for measuring a continuous response are regularly conducted in health sciences to evaluate agreement of a method with itself and agreement between methods. Notwithstanding their wide usage, the design of such studies, in particular, the sample size determination, has not been addressed in the literature when the goal is the simultaneous evaluation of intra- and int...

BACKGROUND: In epidemiologic studies researchers are often interested in detecting confounding (when a third variable is both associated with and affects associations between the outcome and predictors). Confounder detection methods often compare regression coefficients obtained from "crude" models that exclude the possible confounder(s) and "adjusted" models that include the variable(s). One s...

This paper investigates a change-point estimation problem in the context of high-dimensional Markov random field models. Change-points represent a key feature in many dynamically evolving network structures. The change-point estimate is obtained by maximizing a profile penalized pseudo-likelihood function under a sparsity assumption. We also derive a tight bound for the estimate, up to a logari...