MedZIM: Mediation analysis for Zero-Inflated Mediators with applications to microbiome data

The human microbiome can contribute to the pathogenesis of many complex diseases such as cancer and Alzheimer's disease by mediating disease-leading causal pathways. However, standard mediation analysis is not adequate in the context of microbiome data due to the excessive number of zero values in the data. Zero-valued sequencing reads, commonly observed in microbiome studies, arise for technical and/or biological reasons. Mediation analysis approaches for analyzing zero-inflated mediators are still lacking largely because of challenges raised by the zero-inflated data structure: (a) disentangling the mediation effect induced by the point mass at zero; and (b) identifying the observed zero-valued data points that are actually not zero (i.e., false zeros). We develop a novel mediation analysis method under the potential-outcomes framework to fill this gap. We show that the mediation effect of the microbiome can be decomposed into two components that are inherent to the two-part nature of zero-inflated distributions. The first component corresponds to the mediation effect attributable to a unit-change over the positive relative abundance and the second component corresponds to the mediation effect attributable to discrete binary change of the mediator from zero to a non-zero state. With probabilistic models to account for observing zeros, we also address the challenge with false zeros. A comprehensive simulation study and the applications in two real microbiome studies demonstrate that our approach outperforms existing mediation analysis approaches.Comment: Corresponding: Zhigang L

Mapping Perspectives on the EU as Mediator

Research on the European Union’s role as a meditator is nascent. It predominantly focuses on case studies or is cursorily embedded within wider research on the European Union (EU) as a crisis manager. Moreover, there is a significant disconnect between the established studies on mediation based in Conflict Analysis Studies and the EU’s foreign and security policy situated in Security Studies. Thus, there is a dearth of systematic engagement on the issue of EU mediation, although the EU often uses the language of mediation as a key component of its external commitments to conflict prevention, transformation and resolution. While advancements in mediation research suggest that there are certain determinants of mediation, and highlight key features that support and impede actors during conflict, this has not been systematically applied to the EU. Consequently, a key task of this workshop was to establish conceptual clarity and practical information about on the EU’s mediation roles. As a starting point, this workshop took stock of EU mediation knowledge from the perspective of different actors including academics, civil society and policy practitioners. In particular, it explored the limited academic engagement with this particular aspect of EU foreign and security policy. Additionally, the workshop critically interrogated how the EU understood its role in international mediation practice by exploring its capabilities and infrastructure and thereby locating opportunities and constraints to it performance. By bringing together various perspectives these discussions generated critical insights into where the remaining gaps in knowledge lay and the possibilities of academic partnerships with practitioners and policymakers to create new knowledge for Security and Conflict Analysis Studies

Clarifying causal mediation analysis for the applied researcher: Defining effects based on what we want to learn

The incorporation of causal inference in mediation analysis has led to theoretical and methodological advancements -- effect definitions with causal interpretation, clarification of assumptions required for effect identification, and an expanding array of options for effect estimation. However, the literature on these results is fast-growing and complex, which may be confusing to researchers unfamiliar with causal inference or unfamiliar with mediation. The goal of this paper is to help ease the understanding and adoption of causal mediation analysis. It starts by highlighting a key difference between the causal inference and traditional approaches to mediation analysis and making a case for the need for explicit causal thinking and the causal inference approach in mediation analysis. It then explains in as-plain-as-possible language existing effect types, paying special attention to motivating these effects with different types of research questions, and using concrete examples for illustration. This presentation differentiates two perspectives (or purposes of analysis): the explanatory perspective (aiming to explain the total effect) and the interventional perspective (asking questions about hypothetical interventions on the exposure and mediator, or hypothetically modified exposures). For the latter perspective, the paper proposes tapping into a general class of interventional effects that contains as special cases most of the usual effect types -- interventional direct and indirect effects, controlled direct effects and also a generalized interventional direct effect type, as well as the total effect and overall effect. This general class allows flexible effect definitions which better match many research questions than the standard interventional direct and indirect effects

Mediation, Walrasian Tatonement, and Negotiations as an Exchange Economy

Alternative dispute resolution (ADR) procedures, such as mediation and arbitration, are becoming increasingly used to help resolve disputes in a variety of arenas. Among ADR procedures, mediation is the most utilized yet least analyzed procedure. This article examines negotiations and dispute resolution using the tools of general equilibrium theory. Specifically, mediators function as the Walrasian auctioneers of exchange theory by altering trade-off rates among bargaining issues. In this way, mediators facilitate a process leading towards voluntary settlement. This idea of Walrasian mediation is supported by the literature on mediation and mediator techniques, and so this insight opens up mediation to much more rigorous economic analysis. Among the implications of this approach are: 1) successful mediation leads to Pareto efficient settlements; 2) non-neutral mediators—those with a stake in the outcome—can guide negotiators towards preferred outcomes by introducing resources into mediation; 3) mediation Pareto dominates arbitration for resolving disputes.

Landscape of Supersymmetric Particle Mass Hierarchies in Deflected Mirage Mediation

With the aim of uncovering viable regions of parameter space in deflected mirage mediation (DMM) models of supersymmetry breaking, we study the landscape of particle mass hierarchies for the lightest four non-Standard Model states for DMM models and compare the results to that of minimal supergravity/constrained MSSM (mSUGRA/CMSSM) models, building on previous studies of Feldman, Liu, and Nath. Deflected mirage mediation is a string-motivated scenario in which the soft terms include comparable contributions from gravity mediation, gauge mediation, and anomaly mediation. DMM allows a wide variety of phenomenologically preferred models with light charginos and neutralinos, including novel patterns in which the heavy Higgs particles are lighter than the lightest superpartner. We use this analysis to motivate two DMM benchmark points to be used for more detailed collider studies. One model point has a higgsino-dominated lightest superpartner and a compressed yet heavy spectrum, while the other has a stau NLSP and similar features to mSUGRA/CMSSM models, but with a slightly less stretched spectrum.Comment: 33 pages, 23 figure

Graphical models for mediation analysis

Mediation analysis seeks to infer how much of the effect of an exposure on an outcome can be attributed to specific pathways via intermediate variables or mediators. This requires identification of so-called path-specific effects. These express how a change in exposure affects those intermediate variables (along certain pathways), and how the resulting changes in those variables in turn affect the outcome (along subsequent pathways). However, unlike identification of total effects, adjustment for confounding is insufficient for identification of path-specific effects because their magnitude is also determined by the extent to which individuals who experience large exposure effects on the mediator, tend to experience relatively small or large mediator effects on the outcome. This chapter therefore provides an accessible review of identification strategies under general nonparametric structural equation models (with possibly unmeasured variables), which rule out certain such dependencies. In particular, it is shown which path-specific effects can be identified under such models, and how this can be done

Survival mediation analysis with the death-truncated mediator: The completeness of the survival mediation parameter

In medical research, the development of mediation analysis with a survival outcome has facilitated investigation into causal mechanisms. However, studies have not discussed the death-truncation problem for mediators, the problem being that conventional mediation parameters cannot be well-defined in the presence of a truncated mediator. In the present study, we systematically defined the completeness of causal effects to uncover the gap, in conventional causal definitions, between the survival and nonsurvival settings. We proposed three approaches to redefining the natural direct and indirect effects, which are generalized forms of the conventional causal effects for survival outcomes. Furthermore, we developed three statistical methods for the binary outcome of the survival status and formulated a Cox model for survival time. We performed simulations to demonstrate that the proposed methods are unbiased and robust. We also applied the proposed method to explore the effect of hepatitis C virus infection on mortality, as mediated through hepatitis B viral load