This paper shows how the probability, for a random confounding factor to reverse the estimate of ordinary regression, decreases exponentially with the sample size.

A random sample size version of the central limit theorem is obtained for a general class of symmetric statistics based on uniform spacings. An important application to goodness of fit test for a Poisson process is discussed.

We prove the following conjecture of Narayana: there are no nontrivial dominance reene-ments of the Smirnov two-sample test if and only if the two sample sizes are relatively prime. We also count the number of natural signiicance levels of the Smirnov two-sample test in terms of the sample sizes and relate this to the Narayana conjecture. In particular, Smirnov tests with relatively prime sampl...

OBJECTIVE To investigate the use of helmets for cyclists choosing to use BIXI bikes in comparison to personal bike riders in the City of Toronto. DESIGN Cross-sectional study design. SETTING Cyclists were observed in Toronto, Canada. PARTICIPANTS Of the 6732 sample size, 306 cyclists on BIXI bikes and 6426 personal bike riders were observed. OUTCOME MEASURE The outcome of interest was h...

This procedure computes power and sample size for non-inferiority tests in two-sample designs in which the outcome is a continuous normal random variable. Measurements are made on individuals that have been randomly assigned to one of two groups. This is sometimes referred to as a parallel-groups design. This design is used in situations such as the comparison of the income level of two regions...

In this paper we use simulations to compare the performance of new goodness-of-fit tests based on weighted statistical processes to three currently available tests: the Hosmer-Lemeshow decile-of-risk test; the Pearson chi-square, and the unweighted sum-of-squares tests. The simulations demonstrate that all tests have the correct size. The power for all tests to detect lack-of-fit due to an omit...

There is considerable interest in methods that use accumulated data to modify trial sample size. However, sample size re-estimation in group sequential designs has been controversial. We describe a method for sample size re-estimation at the penultimate stage of a group sequential design that achieves specified power against an alternative hypothesis corresponding to the current point estimate ...

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...