A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

The identification and understanding of gene-environment interactions can provide insights into the pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains a challenge since statistical power is often limited, the specification of environmental effects is nontrivial, and such misspecifications can lead to false positive findings. To address the lack of statistical power, recent methods aim to identify interactions on an aggregated level using, for example, polygenic risk scores. While this strategy increases power to detect interactions, identifying contributing key genes and pathways is difficult based on these global results.Here, we propose RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing framework for quantitative traits that is based on sample splitting and robust test statistics. RITSS can incorporate multiple genetic variants and/or multiple environmental factors. Using sample splitting, a screening step enables the selection and combination of potential interactions into scores with improved interpretability, based on the user’s unrestricted choices for statistical/machine learning approaches. In the testing step, the application of robust test statistics minimizes the susceptibility of the results to main effect misspecifications.Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios. In an application to lung function phenotypes and human height in the UK Biobank, RITSS identified genome-wide significant interactions with subcomponents of genetic risk scores. While the contributing single variant interactions are moderate, our analysis results indicate interesting interaction patterns that result in strong aggregated signals that provide further insights into gene-environment interaction mechanisms.

Validating Communicative Tests of Reading and Language Use of Classical Greek

This paper builds on the work presented previously in this journal by Poupounaki-Lappa et al. (2021), which described the development of a communicative test of Reading and Language Use of Classical Greek calibrated to the Common European Framework of Reference (CEFR) at levels A1 and A2 (Council of Europe, 2001). In the current paper, the two tests of Classical Greek are calibrated both together and to the CEFR. In addition to describing the methodology for comparing the two separate tests of Classical Greek, the paper is also designed to be of interest to educators of other classical languages. It is hoped that they may find it useful not only by facilitating robust test design, but also by demonstrating the methods by which tests can be linked together on a common scale (as with the CEFR) or linking tests one to another (e.g., different end-of-year tests, at different points in time).

Factors Affecting the Trade Dependence Relationship of Asian Countries with China: Implications for China’s Belt and Road Initiative

China’s Belt and Road Initiative (B&R) has received much doubts about its impact on Asian countries. This paper studies the B&R effect from a new perspective of the trade dependence relationship, and explores this B&R impact on the influencing factors of the degree of trade dependence. By implementing a series of grouping analyses on influencing factors, this paper analyses the impact of four national characteristics, including Asian countries’ income levels, geographical location characteristics, social development levels and intimacy with China, and finally gives a robust test by combining alternative indicators of trade dependence degree based on information entropy. The empirical results show that trade dependence degree has increased after implementing the B&R, but its downward growth rate shows that the B&R has not taken over the trade dependence. The inhibiting effects of energy exports on the degree of trade dependence deny the trade binding hypothesis due to the increasing energy of export trade. Trade openness and infrastructure development had a negative effect on the degree of trade dependence, while their cross-product term weakened their respective inhibitory effects, and even more after B&R. Meanwhile, the asymmetry of trade and FDI have a significantly positive impact on the degree of trade dependence. Moreover, grouping national characteristics will bring the promoting or inhibiting effects of these influencing factors on the degree of trade dependence. The robust test presents conclusions. This paper enriches the research content on the B&R, and the findings can provide some implications on the selection of trade partners and the sustainable development of the B&R.

Passion in the pit: the effects of harmonious and obsessive passion on nurse burnout

PurposeAnecdotal and survey reports indicate that nurses are suffering increased stress and burnout due to the coronavirus disease (COVID-19) pandemic. Therefore, this study investigated two forms of passion, harmonious and obsessive passion, as resources that may indirectly predict two forms of burnout, disengagement and exhaustion, through the mediator of job stress.Design/methodology/approachThe authors tested their hypotheses in a mediation model using a sample of nurses surveyed at three timepoints during the COVID-19 pandemic.FindingsAs hypothesized, harmonious passion indirectly decreased disengagement and exhaustion by decreasing job stress. Contrary to authors’ hypotheses, obsessive passion also indirectly decreased (rather than increased, as hypothesized) both disengagement and exhaustion by decreasing job stress. Harmonious, but not obsessive, passion, was significantly negatively directly related to disengagement and exhaustion.Research limitations/implicationsData were collected during the COVID-19 pandemic, which may have impacted nurses’ work environments and their willingness to respond.Originality/valueThis study extends conservation of resources theory to conceptualize harmonious and obsessive passion as resources with differing outcomes based on their contrasting identity internalization, per the Dualistic Model of Passion. This study also operationalizes burnout more comprehensively by including cognitive and physical exhaustion along with emotional exhaustion, as well as disengagement. By collecting responses at three timepoints, this study provides a more robust test of causality than previous work examining passion and burnout.

A Robust Test for Monotonicity in Asset Returns

In this paper, we propose a robust test of monotonicity in asset returns that is valid under a general setting. We develop a test that allows for dependent data and is robust to conditional heteroskedasticity or heavy-tailed distributions of return differentials. Many postulated theories in economics and finance assume monotonic relationships between expected asset returns and certain underlying characteristics of an asset. Existing tests in literature fail to control the probability of a type 1 error or have low power under heavy-tailed distributions of return differentials. Monte Carlo simulations illustrate that our test statistic has a correct empirical size under all data-generating processes together with a similar power to other tests. Conversely, alternative tests are nonconservative under conditional heteroskedasticity or heavy-tailed distributions of return differentials. We also present an empirical application on the monotonicity of returns on various portfolios sorts that highlights the usefulness of our approach.

Testing for slope heterogeneity in Stata

In this article, we introduce a new community-contributed command, xthst, to test for slope heterogeneity in panels with many observations over cross-sectional units and time periods. The command implements such a test, the delta test (Pesaran and Yamagata, 2008, Journal of Econometrics 142: 50–93). Under its null, slope coefficients are homogeneous across cross-sectional units. Under the alternative, slope coefficients are heterogeneous in the cross-sectional dimension. xthst also includes two extensions. The first is a heteroskedasticity- and autocorrelation-consistent robust test along the lines of Blomquist and Westerlund (2013, Economics Letters 121: 374–378). The second extension is a cross-sectional-dependence robust version. We discuss all tests and present examples using an economic growth model. A Monte Carlo simulation shows that the size and the power behave as expected.