Estimation and goodness-of-fit procedures for Farlie–Gumbel–Morgenstern bivariate copula of order statistics

In this study, we provide the Farlie–Gumbel–Morgenstern bivariate copula of rth and sth order statistics. The main emphasis in this study is on the inference procedure which is based on the maximum pseudo-likelihood estimate for the copula parameter. As for the methodology, goodness-of-fit test statistic for copulas which is based on a Cramér–von Mises functional of the empirical copula process is applied for selecting an appropriate model by bootstrapping. An application of the methodology to simulated data set is also presented.     

Robust gene–environment interaction analysis using penalized trimmed regression

ABSTRACT

In biomedical and epidemiological studies, gene–environment (G–E) interactions have been shown to importantly contribute to the etiology and progression of many complex diseases. Most existing approaches for identifying G–E interactions are limited by the lack of robustness against outliers/contaminations in response and predictor spaces. In this study, we develop a novel robust G–E identification approach using the trimmed regression technique under joint modelling. A robust data-driven criterion and stability selection are adopted to determine the trimmed subset which is free from both vertical outliers and leverage points. An effective penalization approach is developed to identify important G–E interactions, respecting the ‘main effects, interactions’ hierarchical structure. Extensive simulations demonstrate the better performance of the proposed approach compared to multiple alternatives. Interesting findings with superior prediction accuracy and stability are observed in the analysis of The Cancer Genome Atlas data on cutaneous melanoma and breast invasive carcinoma.     

Improving early phase oncology clinical trial design: The case for finding the optimal biological dose

Historically early phase oncology drug development programmes have been based on the belief that “more is better”. Furthermore, rule-based study designs such as the “3 + 3” design are still often used to identify the MTD. Phillips and Clark argue that newer Bayesian model-assisted designs such as the BOIN design should become the go to designs for statisticians for MTD finding. This short communication goes one stage further and argues that Bayesian model-assisted designs such as the BOIN12 which balances risk-benefit should be included as one of the go to designs for early phase oncology trials, depending on the study objectives. Identifying the optimal biological dose for future research for many modern targeted drugs, immunotherapies, cell therapies and vaccine therapies can save significant time and resources.     

No mood effects in the field: The case of car inspections

We study mood effect in the field to measure its economic impact and address shortcomings in the existing literature, which typically uses one single mood proxy and ignores selection effects. Using over 50 million car inspections in Sweden and England and multiple mood proxies, we study whether car inspectors are more lenient on good mood days and if car owners self-select into those days. We find evidence of a “Friday effect” in England and a small selection bias, but no support for consistent mood effect. Our findings highlight the importance of considering the expectations of rational actors who may exploit mood effect and the need to study mood in the field using different settings and multiple proxies to avoid hasty conclusions.     

Impact of technology-intensive exports on GDP of Western Balkan Countries

This paper aims to determine, by means of regression analysis, which exported product groups, categorized according to their technological intensity, have the greatest effect on the movements in the volume of GDP p/c of the Western Balkan Countries (WBCs). The analysis, based on statistical-econometric methodology, includes 16 commodity groups per each WBC (Albania; Bosnia and Herzegovina; Croatia; FYR Macedonia; Montenegro; Serbia). The data were collected and presented in accordance with the HS4 system classification, which is also used for development of the ITC’s Trade Map. The results of the analysis show that those commodity groups produced by medium-low and low technology industries have the greatest effect on the change in the volume of GDP p/c in all WBCs in the period 2005–2015.     

Hugh George Brennan: Glasgow University’s First Lecturer in Russian

To date little has been known, and less written, about the life of Hugh George Brennan, Glasgow University's first lecturer in Russian. The uncovering of previously unused Russian and British sources throwing fresh light on his life, intellectual development and occupations has made possible a fuller assessment of a significant figure in Glasgow's contribution to Slavonic Studies. Brennan lived and taught in Russia for 20 years. The resulting intense and unusually intimate experience of Russian life probably explains unconventional aspects of his Glasgow appointment. Brennan was an undoubted educational and social success in Russia. Events in the shape of the February Revolution of 1917 forced him to return to Britain. Glasgow's timely offer of a new position was the start of a very different life. This aspect of Brennan's career is reviewed mainly through his commitment to extensive public activities.     

The effect of board size on shareholder value: Evidence from bank mergers and acquisitions

This study examines the effect of board size on the economic impact of bank mergers and acquisitions (M&A) in the US. Using a hand-collected dataset of 508 M&A between 2012 and 2018, we find that board size is negatively related to acquirer excess returns. In an additional analysis, we show that large boards have positive value implications for banks that combine the CEO and chairman roles as well as for large banks. Our findings indicate that a “one-size-fits-all” approach to board size is not necessarily in the interests of shareholders; instead, a more flexible and proactive formulation is needed.