Seungho Kang

Most statistical methods for the analysis of correlated binary data are based on asymptotic theory. Therefore it is important to generate correlated binary data efficiently for Monte Carlo simulation studies to investigate the finite sample performance of these methods. This article provides a simple method for generating correlated binary data with a given joint distribution. The key idea is to consider k-variate binary data as a multinomial distribution with 2k possible outcomes.

Many scientific problems can be formulated in terms of a statistical model indexed by parameters, only some of which are of scientific interest and the other parameters, called nuisance parameters, are not of interest in themselves. For testing the Hardy-Weinberg law, a relation among genotype and allele probabilities is of interest and allele probabilities are of no interest and now nuisance parameters. In this paper we investigate how the size (the maximum of the type I error rate over the nui

The most widely used design for a Phase III comparative study for demonstrating the biosimilarity between a biosimilar product and a renovator biological product is the equivalence trial, whose aim is to show that the difference between two population means of a primary endpoint is less than a prespecified equivalence margin. A well-known sample size formula for the equivalence trial is given by [Formula: see text] Since this formula is obtained based on the approximate power rather than the exa

The objective of this study was to develop a model for predicting Korean adult consumers who frequently eat food-away-from-home. A total of 7,032 adults aged 19 years and older from the 2001 National Health and Nutrition Survey in Korea were used as subjects. The data were analyzed using a data mining procedure including logistic regression and decile analysis. The model developed in the study was proven to be valid in predicting the consumers who frequently eat food-away-from home(once a day or

Data observed in multiregional clinical trials are structurally hierarchical in the sense that the patient population consists of several regions and patients are nested within their own regions. To reflect such hierarchical structure, in this article, we propose two-level hierarchical linear models in which the level-1 model is based on patient-level data such as treatment indicator and age, and the level-2 model is based on region-level data such as medical practices. The fixed effect model an

This article deals with the dependency(ies) of noninferiority test(s) when the two confidence interval method is employed. There are two different definitions of the two confidence interval method. One of the objectives of this article is to sort out some of the confusion in these two different definitions. In the first definition the two confidence interval method is considered as the fixed margin method that treats a noninferiority margin as a fixed constant after it is determined based on his

A regulatory agency usually requires two independent positive trials of the same new drug for approval. If two different new drugs are approved with the λ-margin approach by using the same active control, it implies that four noninferiority trials share the same active control. Sharing the same active control generates dependencies among trials. In this paper we investigate how much such dependencies inflate the unconditional and conditional across-trial type I error rates, and we propose a new

In this paper we developed exact tests for one sample correlated binary data whose cluster sizes are at most two. Although significant progress has been made in the development and implementation of the exact tests for uncorrelated data, exact tests for correlated data are rare. Lack of a tractable likelihood function has made it difficult to develop exact tests for correlated binary data. However, when cluster sizes of binary data are at most two, only three parameters are needed to characteriz

Multiregional clinical trials have a hierarchical data structure because several regions form a patient population and individual patients are nested within their own regions. Data are obtained from two different levels: regions and patients. To incorporate such a hierarchical structure, hierarchical linear models were proposed for the response variables following a normal distribution by Kim and Kang. In this article, we extend the hierarchical linear models to propose hierarchical generalized

The one of the principles described in ICH E9 is that only results obtained from pre-specified statistical methods in a protocol are regarded as confirmatory evidence. However, in multi-regional clinical trials, even when results obtained from pre-specified statistical methods in protocol are significant, it does not guarantee that the test treatment is approved by regional regulatory agencies. In other words, there is no so-called global approval, and each regional regulatory agency makes its o