Meta-analysis is widely used to synthesize the results of multiple studies. Although meta-analysis is traditionally carried out by combining the summary statistics of relevant studies, advances in technologies and communications have made it increasingly feasible to access the original data on individual participants. In the present paper, we investigate the relative efficiency of analyzing ori...

Description Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (cen...

Time-course microarray studies require a particular modelling of covariance matrices when measures are repeated on the same individuals. Taking into account the within-subject correlation in the test statistics for differential gene expression involves, however, a large number of parameters when a gene-specific approach is used, which often results in a lack of power due to the small number of ...

A novel algorithm is proposed in this paper to solve blind source separation of post-nonlinear convolutive mixtures of non-stationary sources. Both convolutive mixing and post-nonlinear distortion are included in the proposed model. Based on the generalized Expectation-Maximization (EM) algorithm, the Maximum Likelihood (ML) approach is developed to estimate the parameters in the model. A set o...

A novel approach based on fourth order statistics is presented for estimating the parameters of the complex exponential signal model in additive colored Gaussian noise whose autocorrelation function is not known. Monte Carlo simulations demonstrate that the proposed method performs better than an existing method which also utilizes fourth order statistics under the similar noise condition. To d...

Researchers are often interested in testing for measurement invariance with respect to an ordinal auxiliary variable such as age group, income class, or school grade. In a factoranalytic context, these tests are traditionally carried out via a likelihood ratio test statistic comparing a model where parameters differ across groups to a model where parameters are equal across groups. This test ne...

In this paper we address the problem of model-based image segmentation by fitting deformable models to the image data. From uncertain a priori knowledge of the model parameters an initial probability distribution of the model edge in the image is obtained. From the vicinity of the surmised edge local statistics are learned for both sides of the edge. These local statistics provide locally adapt...

medical statistics (biostatistics), as a vital essential part of modem life, does raise some fundamental ethical issues. surprisingly, this aspect seems to have been totally ignored by books on medical ethics. this paper discusses how the statistical aspects affect the ethics. the relation between biostatistics and medical research is explored. all stages of a medical research exercise are vuln...

An important problem in statistics is to obtain information about the form of the population from which the sample is drawn. Goodness of fit test is employed to determine how well the observed sample data "fits" some proposed model. The standard goodness of fit statistics are inappropriate when the parameters of the hypothesized distribution are estimated from the data used for the test. In thi...

Researchers are often interested in testing for measurement invariance with respect to an ordinal auxiliary variable such as age group, income class, or school grade. In a factor-analytic context, these tests are traditionally carried out via a likelihood ratio test statistic comparing a model where parameters differ across groups to a model where parameters are equal across groups. This test n...