Current Directions in Mediation Analysis

ABSTRACT— Mediating variables continue to play an important role in psychological theory and research. A mediating variable transmits the effect of an antecedent variable on to a dependent variable, thereby providing more detailed understanding of relations among variables. Methods to assess mediation have been an active area of research for the last two decades. This paper describes the current state of methods to investigate mediating variables.     

Flexible Mediation Analysis in the Presence of Nonlinear Relations: Beyond the Mediation Formula

In the social sciences, mediation analysis has typically been formulated in the context of linear models using the Baron &; Kenny (1986) Baron, R. M. and Kenny, D. A. 1986. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, 51: 1173–1182. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar] approach. Extensions to nonlinear models have been considered but lack formal justification. By placing mediation analysis within the counterfactual framework of causal inference one can define causal mediation effects in a way that is not tied to a specific statistical model and identify them under certain no unmeasured confounding assumptions. Corresponding estimation procedures using parametric or nonparametric models, based on the so-called mediation formula, have recently been proposed in the psychological literature and made accessible through the R-package mediation. A number of limitations of the latter approach are discussed and a more flexible approach using natural effects models is proposed as an alternative. The latter builds on the same counterfactual framework but enables interpretable and parsimonious modeling of direct and mediated effects and facilitates tests of hypotheses that would otherwise be difficult or impossible to test. We illustrate the approach in a study of individuals who ended a romantic relationship and explore whether the effect of attachment anxiety during the relationship on unwanted pursuit behavior after the breakup is mediated by negative affect during the breakup.     

Sample Size Planning for Detecting Mediation Effects: A Power Analysis Procedure Considering Uncertainty in Effect Size Estimates

Abstract

When planning mediation studies, researchers are often interested in the sample size needed to achieve adequate power for testing mediation. Power depends on population effect sizes, which are unknown in practice. In conventional power analysis, effect size estimates, however, are often used as population values, which could result in underpowered studies. Uncertainty in effect size estimates has been considered in other sample size planning contexts (e.g., t-test, ANOVA), but has not been handled properly for planning mediation studies. In the current study, we proposed an easy-to-use sample size planning method for testing mediation with uncertainty in effect size estimates considered. We conducted simulation studies to demonstrate the impact of uncertainty in effect size estimates on power of testing mediation, and to provide sample size suggestions under different levels of uncertainty. Empirical examples were provided to illustrate the application of our method. R functions and a web application were developed to facilitate implementation.     

The Use of Propensity Scores in Mediation Analysis

Mediation analysis uses measures of hypothesized mediating variables to test theory for how a treatment achieves effects on outcomes and to improve subsequent treatments by identifying the most efficient treatment components. Most current mediation analysis methods rely on untested distributional and functional form assumptions for valid conclusions, especially regarding the relation between the mediator and outcome variables. Propensity score methods offer an alternative whereby the propensity score is used to compare individuals in the treatment and control groups who would have had the same value of the mediator had they been assigned to the same treatment condition. This article describes the use of propensity score weighting for mediation with a focus on explicating the underlying assumptions. Propensity scores have the potential to offer an alternative estimation procedure for mediation analysis with alternative assumptions from those of standard mediation analysis. The methods are illustrated investigating the mediational effects of an intervention to improve sense of mastery to reduce depression using data from the Job Search Intervention Study (JOBS II). We find significant treatment effects for those individuals who would have improved sense of mastery when in the treatment condition but no effects for those who would not have improved sense of mastery under treatment.     

Methods for Mediation Analysis with Missing Data

Despite wide applications of both mediation models and missing data techniques, formal discussion of mediation analysis with missing data is still rare. We introduce and compare four approaches to dealing with missing data in mediation analysis including listwise deletion, pairwise deletion, multiple imputation (MI), and a two-stage maximum likelihood (TS-ML) method. An R package bmem is developed to implement the four methods for mediation analysis with missing data in the structural equation modeling framework, and two real examples are used to illustrate the application of the four methods. The four methods are evaluated and compared under MCAR, MAR, and MNAR missing data mechanisms through simulation studies. Both MI and TS-ML perform well for MCAR and MAR data regardless of the inclusion of auxiliary variables and for AV-MNAR data with auxiliary variables. Although listwise deletion and pairwise deletion have low power and large parameter estimation bias in many studied conditions, they may provide useful information for exploring missing mechanisms.     

Explanation of Two Anomalous Results in Statistical Mediation Analysis

Previous studies of different methods of testing mediation models have consistently found two anomalous results. The first result is elevated Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap tests not found in nonresampling tests or in resampling tests that did not include a bias correction. This is of special concern as the bias-corrected bootstrap is often recommended and used due to its higher statistical power compared with other tests. The second result is statistical power reaching an asymptote far below 1.0 and in some conditions even declining slightly as the size of the relationship between X and M, a, increased. Two computer simulations were conducted to examine these findings in greater detail. Results from the first simulation found that the increased Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap are a function of an interaction between the size of the individual paths making up the mediated effect and the sample size, such that elevated Type I error rates occur when the sample size is small and the effect size of the nonzero path is medium or larger. Results from the second simulation found that stagnation and decreases in statistical power as a function of the effect size of the a path occurred primarily when the path between M and Y, b, was small. Two empirical mediation examples are provided using data from a steroid prevention and health promotion program aimed at high school football players (Athletes Training and Learning to Avoid Steroids; Goldberg et al., 1996), one to illustrate a possible Type I error for the bias-corrected bootstrap test and a second to illustrate a loss in power related to the size of a. Implications of these findings are discussed.     

Well-Being and Physical Health: A Mediation Analysis

This paper’s aim is to propose a mediation framework and test whether lifestyle choices and social capital are pathways through which baseline levels of well-being affect subsequent physical health among older adults. Using large-scale panel data for Australia, we find that past levels of well-being have strong direct effects on present physical health. We also show that more frequent socialization and more frequent participation in physical activity are two pathways through which higher levels of well-being lead to better physical health. These mediating effects vary across gender. Our findings highlight a protective role of subjective well-being in physical health. Interventions taking into account not only the direct but also the indirect effects of well-being are promising avenues for physical health maintenance in the older population.

     

An Evaluation of Two Mediation Techniques,Negotiator Power,and Culture in Negotiation1

This study examines the effects of 4 factors in a mediated transfer‐pricing negotiation: (a) the mediator's suggestion that negotiators have concern for the other (opposing) negotiator; (b) the mediator's proposal of moderate goals; (c) negotiator power; and (d) culture. In the simulated negotiations that were mediated by a corporate official, participants were 374 subjects from Hong Kong and the United States. Negotiators obtained lower joint outcomes when urged by the mediator to show concern for the other than when not given this admonition. When the mediator proposed moderate (vs. high) goals, the negotiators received lower joint outcomes but had a higher opinion of the mediator. While we expected negotiator power (equal vs. unequal) to interact with suggested concern for the other, it did so only for the negotiators' individual outcomes. Finally, culture produced a main effect: Hong Kong negotiators obtained higher joint outcomes than did their U. S. counterparts.     

Mediation Analysis in Social Psychology: Current Practices and New Recommendations

A key aim of social psychology is to understand the psychological processes through which independent variables affect dependent variables in the social domain. This objective has given rise to statistical methods for mediation analysis. In mediation analysis, the significance of the relationship between the independent and dependent variables has been integral in theory testing, being used as a basis to determine (1) whether to proceed with analyses of mediation and (2) whether one or several proposed mediator(s) fully or partially accounts for an effect. Synthesizing past research and offering new arguments, we suggest that the collective evidence raises considerable concern that the focus on the significance between the independent and dependent variables, both before and after mediation tests, is unjustified and can impair theory development and testing. To expand theory involving social psychological processes, we argue that attention in mediation analysis should be shifted towards assessing the magnitude and significance of indirect effects.     

Mediation in custody disputes

This article summarizes the results of an evaluation of mediation services in three court-based programs. Among the issues considered are client evaluations of the mediation experience and their assessments of immediate and long-term effects. Two comparison groups are utilized: parents who contested custody without the offer of court-based mediation and parents who divorced but did not contest custody. Results of the research indicate that mediation provides a valuable compliment to the existing domestic relations court processes. Mediation enjoys high user satisfaction and helps promote compliance with the agreement, a sense of equity, and continued cooperation. Thus, while the expectations of the process should not be overstated, it appears that even a brief mediation with a troubled population can produce modest but positive benefits.     

A Class of Distribution-Free Models for Longitudinal Mediation Analysis

Mediation analysis constitutes an important part of treatment study to identify the mechanisms by which an intervention achieves its effect. Structural equation model (SEM) is a popular framework for modeling such causal relationship. However, current methods impose various restrictions on the study designs and data distributions, limiting the utility of the information they provide in real study applications. In particular, in longitudinal studies missing data is commonly addressed under the assumption of missing at random (MAR), where current methods are unable to handle such missing data if parametric assumptions are violated. In this paper, we propose a new, robust approach to address the limitations of current SEM within the context of longitudinal mediation analysis by utilizing a class of functional response models (FRM). Being distribution-free, the FRM-based approach does not impose any parametric assumption on data distributions. In addition, by extending the inverse probability weighted (IPW) estimates to the current context, the FRM-based SEM provides valid inference for longitudinal mediation analysis under the two most popular missing data mechanisms; missing completely at random (MCAR) and missing at random (MAR). We illustrate the approach with both real and simulated data.     

Social Network Mediation Analysis: A Latent Space Approach

Psychometrika - A social network comprises both actors and the social connections among them. Such connections reflect the dependence among social actors, which is essential for individuals’...     

病症理解与性别权力——基于女性主义的视角

病症理解的唯科学主义倾向反映了医学领域的男性主义思维统治。病症的唯科学理解割裂了病症与不同性别主体的联系;病症的唯科学理解忽视女性经验与情感在医学科学研究中的意义。病症的理解需要范式的根本转变,这种新的范式将不仅应该根据临床界定的疾病状态来理解病症,而且应该根据患者的性别与心理以及他们的生存困境来理解病症。     

Commentary: Using Potential Outcomes to Understand Causal Mediation Analysis

In this commentary, we demonstrate how the potential outcomes framework can help understand the key identification assumptions underlying causal mediation analysis. We show that this framework can lead to the development of alternative research design and statistical analysis strategies applicable to the longitudinal data settings considered by Maxwell, Cole, and Mitchell (2011).     

依恋回避对愤怒抑制的影响:亲密关系权力感的中介作用

依恋回避是指一个人不信任伴侣的好意,防御性地保持行为和情感的独立.愤怒抑制表示抑制愤怒情绪的外在表现.为了探讨依恋回避对愤怒抑制的影响及其内在机制,以具有恋爱经历的成年个体为被试,采用实验法和问卷法,先后对267人、101人、429人进行依恋回避、亲密关系权力感和愤怒抑制的测量,并检验中介作用.结果显示,在亲密关系中:...