On the Multilevel Nature of Meta-Analysis: A Tutorial,Comparison of Software Programs,and Discussion of Analytic Choices

The term “multilevel meta-analysis” is encountered not only in applied research studies, but in multilevel resources comparing traditional meta-analysis to multilevel meta-analysis. In this tutorial, we argue that the term “multilevel meta-analysis” is redundant since all meta-analysis can be formulated as a special kind of multilevel model. To clarify the multilevel nature of meta-analysis the four standard meta-analytic models are presented using multilevel equations and fit to an example data set using four software programs: two specific to meta-analysis (metafor in R and SPSS macros) and two specific to multilevel modeling (PROC MIXED in SAS and HLM). The same parameter estimates are obtained across programs underscoring that all meta-analyses are multilevel in nature. Despite the equivalent results, not all software programs are alike and differences are noted in the output provided and estimators available. This tutorial also recasts distinctions made in the literature between traditional and multilevel meta-analysis as differences between meta-analytic choices, not between meta-analytic models, and provides guidance to inform choices in estimators, significance tests, moderator analyses, and modeling sequence. The extent to which the software programs allow flexibility with respect to these decisions is noted, with metafor emerging as the most favorable program reviewed.     

Contributions to Estimation of Polychoric Correlations

This research concerns the estimation of polychoric correlations in the context of fitting structural equation models to observed ordinal variables by multistage estimation. The first main contribution of this research is to propose and evaluate a Monte Carlo estimator for the asymptotic covariance matrix (ACM) of the polychoric correlation estimates. In multistage estimation, the ACM plays a prominent role, as overall test statistics, derived fit indices, and parameter standard errors all depend on this quantity. The ACM, however, must itself be estimated. Established approaches to estimating the ACM use a sample-based version, which can yield poor estimates with small samples. A simulation study demonstrates that the proposed Monte Carlo estimator can be more efficient than its sample-based counterpart. This leads to better calibration for established test statistics, in particular with small samples. The second main contribution of this research is a further exploration of the consequences of violating the normality assumption for the underlying response variables. We show the consequences depend on the type of nonnormality, and the number and location of thresholds. The simulation study also demonstrates that overall test statistics have little power to detect the studied forms of nonnormality, regardless of the ACM estimator.     

Exploring posttraumatic growth in Tamil children affected by the Indian Ocean Tsunami in 2004

Few studies explore posttraumatic growth (PTG) in children from Eastern cultures. To help address this gap, the present study examined PTG among 177 South Indian children aged 8–17 years who were affected by the 2004 Tsunami. The study identifies the underlying factor structure of the Tamil version of the Revised Posttraumatic Growth Inventory for Children (PTGI‐C‐R), and aims to explore the prevalence of PTG, the relationship between distress and growth, and gender and age differences in PTG. The results of the principal component analysis indicated a two‐factor structure with an interpersonal and a person‐centred dimension of growth. The total scores of the Tamil PTGI‐C‐R were positively associated with posttraumatic stress symptoms (PTSS) and age. Moreover, there was a significant relationship between age and the person‐centred growth subscale. Non‐parametric tests found no gender differences in perceived growth. The role of socio‐cultural factors on the nature of PTG is discussed.     

Pentecostal Gift to Christian Unity: Its Possibility in the New Global Context

Church unity has been much discussed, particularly around the centenary of the Edinburgh Missionary Conference. Pentecostalism, as a new player in today's global Christianity, comes with its unique potential toward church unity and corporation. This study identifies three such gifts: numerical growth, spontaneous ecumenicity through worship, and missional cooperation. The study concludes with a self‐critical caution for fellow Pentecostals and the world church so that these gifts would be strengthened.     

评价中心的构想效度和结构模型

采用多质多法和验证性因素分析的方法,对以无领导小组讨论、文件筐和人格测验构成的一个评价中心的构想效度和结构模型进行了研究。通过对136名被试在四个测评维度上的施测,其结果表明,在评价中心中会聚效度低于区分效度,影响评价中心测评结果的主要因素是测评方法而不是测评维度,从而得到了一个以测评方法为潜变量的评价中心结构模型。从该结构模型来看,评价中心之所以起作用是由于其多个测评方法(情景)的结果。表明测评情景对于构建评价中心有着至关重要的作用。     

Predicting Change in Parenting Stress Across Early Childhood: Child and Maternal Factors

This study examined maternal parenting stress in a sample of 430 boys and girls including those at risk for externalizing behavior problems. Children and their mothers were assessed when the children were ages 2, 4, and 5. Hierarchical linear modeling (HLM) was used to examine stability of parenting stress across early childhood and to examine child and maternal factors predicting parenting stress at age 2 and changes in parenting stress across time. Results indicated that single parenthood, maternal psychopathology, child anger proneness, and child emotion dysregulation predicted 2-year parenting stress. Child externalizing behaviors predicted initial status and changes across time in parenting stress. Stability of parenting stress was dependent upon child externalizing problems, as well as interactions between child externalizing problems and gender, and child externalizing problems and emotion regulation. Results are discussed in the context of mechanisms by which parenting stress may influence the development of child externalizing behaviors.     

Individual differences in risk perception versus risk taking: handedness and interhemispheric interaction

Research indicates that right-hemisphere mechanisms are specifically sensitive to and averse to risk. Research also indicates that mixed degree of handedness is associated with increased access to right hemisphere processing. Accordingly, it was predicted that mixed-handers would exhibit greater risk aversion. Participants were presented with various risky activities and were asked to rate (i) the perceived risk, (ii) the perceived benefit, and (iii) their likelihood to engage in each activity. No handedness differences were found for any of these ratings. Regression analyses, however, indicated that the likelihood to engage in risky activities was predicted primarily by the perceived risks in mixed-handers and by the perceived benefits in strong-handers.     

Understanding the emergence of modularity in neural systems

Modularity in the human brain remains a controversial issue, with disagreement over the nature of the modules that exist, and why, when, and how they emerge. It is a natural assumption that modularity offers some form of computational advantage, and hence evolution by natural selection has translated those advantages into the kind of modular neural structures familiar to cognitive scientists. However, simulations of the evolution of simplified neural systems have shown that, in many cases, it is actually non-modular architectures that are most efficient. In this paper, the relevant issues are discussed and a series of simulations are presented that reveal crucial dependencies on the details of the learning algorithms and tasks that are being modelled, and the importance of taking into account known physical brain constraints, such as the degree of neural connectivity. A pattern is established which provides one explanation of why modularity should emerge reliably across a range of neural processing tasks.