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The intraclass correlation coefficient ρ is used as a measure of the degree of resemblance among family members with respect to some biological or psychological attribute, such as blood pressure level or IQ. Many studies have been done in the area. However, a significant gap in the literature is that few statistics are available to test the significance ( H 0 : ρ = 0 against H A : ρ ≠ 0 ) of this important biological measure and no study is available as to the performance of these statistics with respect to level and power. In this paper we develop three large sample test statistics and compare these, in terms of level and power, using extensive simulation studies of these, the Wald test developed in this paper is found to have a very simple form and highest power while maintaining level well. [ABSTRACT FROM AUTHOR]

The problem of model selection in regression analysis through the use of forward selection, backward elimination, and stepwise selection has been well explored in the literature. The main assumption in this, of course, is that the data are normally distributed and the main tool used here is either a t test or an F test. However, the properties of these model selection procedures are not well-known. The purpose of this paper is to study the properties of these procedures within generalized linear regression models, considering the normal linear regression model as a special case. The main tool that is being used is the score test. However, the F test and other large sample tests, such as the likelihood ratio and the Wald test, the AIC, and the BIC, are included for the comparison. A systematic study, through simulations, of the properties of this procedure was conducted, in terms of level and power, for symmetric and asymmetric distributions, such as normal, Poisson, and binomial regression models. Extensions for skewed distributions, over-dispersed Poisson (the negative binomial), and over-dispersed binomial (the beta-binomial) regression models, are also given and evaluated. The methods are applied to analyze two health datasets. [ABSTRACT FROM AUTHOR]

The generalized Gamma distribution is widely used in survival analysis, engineering and economics, and it includes the Gamma distribution as a special case. In real life applications, the Generalized Gamma distribution may be an unnecessarily complicated distribution to fit when one of the simpler models may be sufficient to analyze the data. The aim of this paper is to develop tests of goodness of fit of the two parameter gamma distribution against its three parameter counterpart. Specifically, we develop Wald, C (α) , score, likelihood ratio, and gradient tests. These tests are then compared in terms of empirical size and power using a simulation study. [ABSTRACT FROM AUTHOR]

Many problems in biomedical and other sciences are subject to biased estimates (maximum likelihood or of similar types). In two seminal papers Cox and Snell (1968) and Firth (1993) deal with first order bias of maximum likelihood estimates. Cox and Snell obtain a correction term that corrects, approximately, first order bias and Firth uses an adjustment to the score function; the solution of the estimating equation obtained by solving the adjusted score function to zero, removes the first order bias of the maximum likelihood estimates approximately. In many applications authors use one of these two procedures for bias correction without being aware that the other exists or whether these two procedures are equivalent. In this paper we investigate the equivalence issue of the two methods through theoretical analysis, simulation study and data analysis. We show that the two methods yield either exactly the same estimates or that the preventive method has some edge over the other. [ABSTRACT FROM AUTHOR]

Motivation Under two biologically different conditions, we are often interested in identifying differentially expressed genes. It is usually the case that the assumption of equal variances on the two groups is violated for many genes where a large number of them are required to be filtered or ranked. In these cases, exact tests are unavailable and the Welch's approximate test is most reliable one. The Welch's test involves two layers of approximations: approximating the distribution of the statistic by a t -distribution, which in turn depends on approximate degrees of freedom. This study attempts to improve upon Welch's approximate test by avoiding one layer of approximation. Results We introduce a new distribution that generalizes the t -distribution and propose a Monte Carlo based test that uses only one layer of approximation for statistical inferences. Experimental results based on extensive simulation studies show that the Monte Carol based tests enhance the statistical power and performs better than Welch's t -approximation, especially when the equal variance assumption is not met and the sample size of the sample with a larger variance is smaller. We analyzed two gene-expression datasets, namely the childhood acute lymphoblastic leukemia gene-expression dataset with 22 283 genes and Golden Spike dataset produced by a controlled experiment with 13 966 genes. The new test identified additional genes of interest in both datasets. Some of these genes have been proven to play important roles in medical literature. Availability and implementation R scripts and the R package mcBFtest is available in CRAN and to reproduce all reported results are available at the GitHub repository, https://github.com/iullah1980/MCTcodes. Supplementary information Supplementary data is available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

A V gene phage-display antibody fragments library is developed from patients having systemic lupus erythematose with antiprothrombin antibodies, which is used for studying their function and mechanism in relation to kringle 2 domain of prothrombin. The study can help in defining the pathological significance in relevant animal models.

Research demonstrates that recombinant proteolytic antibody light chains hydrolyze beta-amyloid, which can be a therapeutic for Alzheimer's disease. Results show that the antibody light chains cleave at the alpha-secretase site and carboxyl terminal site of beta-amyloid.