This procedure computes power and sample size for superiority by a margin 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...

The trustworthiness of meta-analysis, a set of techniques used to quantitatively combine results from different studies, has recently been questioned. Problems with meta-analysis stem from bias in selecting studies to include in a meta-analysis and from combining study results when it is inappropriate to do so. Simple graphical techniques address these problems but are infrequently applied. Fun...

where p above is the density function if X is continuous and the mass function if X is discrete. The MLE is denoted θ̂ or θ̂n if we wish to emphasize the sample size. Above, we suppress the dependency of L on X1, . . . , X (n) to emphasize that we are treating the likelihood as a function of θ. Note that both X and θ may be scalars or vectors (not necessarily of the same dimension) and that L may...

We consider the problem of comparing noisy functions, here trial-averaged neuronal firing-rate curves, across multiple experimental conditions. Of interest are comparisons both within neurons and also among populations of individually recorded neurons. We propose likelihood ratio tests to perform comparisons either pointwise or globally over the entire experimental time. A simulation study of p...

• We have evaluated the performance of these diagnoses in three scenario created in R 3.1.0:  Scenario 1: Insufficient burn-in + large sample size for outcome evaluation (20,000)  Scenario 2: Insufficient burn-in + high auto-correlation in the Markov Chain (0.8)  Scenario 3: Insufficient burn-in + correlated outcomes Laliman V1, Roïz J2 1Ensai student, Bruz, France; 2Creativ-Ceutical, London...

The minimum clinically important difference (MCID) between treatments is recognized as a key concept in the design and interpretation of results from a clinical trial. Yet even assuming such a difference can be derived, it is not necessarily clear how it should be used. In this paper, we consider three possible roles for the MCID. They are: (1) using the MCID to determine the required sample si...

Before-and-after safety studies are becoming more desirable in lieu of traditional cross-sectional studies in establishing crash modification factors, especially after the introduction of the first version of the Highway Safety Manual (2010). We present a simple method for estimating necessary sample sizes to obtain a target precision or power when the effect is represented as a proportional ch...

In comparing or assessing methods of treatment it is vital that the appropriate number of patients is selected in order to ensure that the conclusions drawn are statistically viable. This annotation describes the relevance of a statistical power analysis in the context of hypothesis testing to the determination of the optimal sample size of a study. The power of the test indicates how likely it...

The paper reviews both the influencing factors and calculation strategies of sample size determination for survey research. It indicate the factors that affect the sample size determination procedure and explains how. It also provides calculation methods (including formulas) that can be applied directly and easily to estimate the sample size needed in most popular situations.

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...