State-trace analysis is a non-parametric method that can identify the number of latent variables (dimensionality) required to explain the effect of two or more experimental factors on performance. Heathcote, Brown, and Prince (submitted) recently proposed a Bayes Factor method for estimating the evidence favoring one or more than one latent variable in a state-trace experiment, known as Bayesia...

A good estimate of the design effect is critical for calculating the most efficient sample size for cluster surveys. We reviewed the design effects for seven nutrition and health outcomes from nine population-based cluster surveys conducted in emergency settings. Most of the design effects for outcomes in children, and one-half of the design effects for crude mortality, were below two. A reasse...

BACKGROUND Cluster-randomized trials, in which health interventions are allocated randomly to intact clusters or communities rather than to individual subjects, are increasingly being used to evaluate disease control strategies both in industrialized and in developing countries. Sample size computations for such trials need to take into account between-cluster variation, but field epidemiologis...

BACKGROUND Random errors in measurement of a risk factor will introduce downward bias of an estimated association to a disease or a disease marker. This phenomenon is called regression dilution bias. A bias correction may be made with data from a validity study or a reliability study. AIMS AND METHODS In this article we give a non-technical description of designs of reliability studies with e...

The attribute Conforming Run Length (CRL) control chart has attracted increasing research interests in Statistical Process Control (SPC). It decides the process status based on the interval or distance between two nonconforming units. This article proposes a Generalized CRL chart (namely GCRL chart) for monitoring the mean of a measurable quality characteristic x under 100% inspection. To run a...

A pilot study asks whether something can be done, should the researchers proceed with it, and if so, how. However, a pilot study also has a specific design feature; it is conducted on a smaller scale than the main or full-scale study. In other words, the pilot study is important for improvement of the quality and efficiency of the main study. In addition, it is conducted in order to assess the ...

Recent studies have shown the X-bar control chart with variable sampling interval detects shifts in the process mean faster than the traditional X-bar chart. These studies are usually based on the assumption that the process data are independently and normally distributed. However, many situations in practice violate these assumptions. In this study, a methodology is developed to economically ...

Appendix 1: sample size requirements for instrumental variable analysis with genetic instruments For given Type 1 and Type 2 error probabilities and study design, the sample size required to detect an effect of size d is proportional to 1/d 2 V, where V is the Fisher information (expectation of minus the second derivative of the log-likelihood of the effect size) from a single observation. For ...