The strength of the statistical evidence in a sample of data that favors one composite hypothesis over another may be quantified by the likelihood ratio using the parameter value consistent with each hypothesis that maximizes the likelihood function. Unlike the p-value and the Bayes factor, this...

We consider tests of hypotheses when the parameters are not identifiable under the null in semiparametric models, where regularity conditions for profile likelihood theory fail. Exponential average tests based on integrated profile likelihood are constructed and shown to be asymptotically...

An important goal of research involving gene expression data for outcome prediction is to establish the ability of genomic data to define clinically relevant risk factors. Recent studies have demonstrated that microarray data can successfully cluster patients into low and high risk categories....

When data are missing, analyzing records that are completely observed may cause bias or ineffciency. Existing approaches in handling missing data include likelihood, imputation and inverse probability weighting. In this paper, we propose three estimators inspired by deleting some completely...

Purpose – The purpose of the research paper is to provide the humanitarian logistics community with an overall picture about competencies and skills in humanitarian logistics and if there is a lack of professionalization of the logistics function in humanitarian context from an international...

In the signal detection paradigm, the non-parametric index of sensitivity A ′, as first introduced by Pollack and Norman (1964), is a popular alternative to the more traditional d ′ measure of sensitivity. Smith (1995) clarified a confusion about the interpretation of A ′ in relation to...

Although the Bock–Aitkin likelihood-based estimation method for factor analysis of dichotomous item response data has important advantages over classical analysis of item tetrachoric correlations, a serious limitation of the method is its reliance on fixed-point Gauss-Hermite (G-H) quadrature...

Although the Bock–Aitkin likelihood-based estimation method for factor analysis of dichotomous item response data has important advantages over classical analysis of item tetrachoric correlations, a serious limitation of the method is its reliance on fixed-point Gauss-Hermite (G-H) quadrature...

Data collected through Web surveys, in general, do not adopt traditional probability-based sample designs. Therefore, the inferential techniques used for probability samples may not be guaranteed to be correct for Web surveys without adjustment, and estimates from these surveys are likely to be...

Most of the system dynamics studies that evaluate decision making in complex dynamic task focus on the evaluation of performance over repeated trials and on the effectiveness of different instructional strategies as far as performance is concerned. Especially when a strategy seems to yield...