Effectiveness of combinations of Gaussian graphical models for model building

Combining statistical models is an useful approach in all the research area where a global picture of the problem needs to be constructed by binding together evidence from different sources [M.S. Massa and S.L. Lauritzen Combining Statistical Models, M. Viana and H. Wynn, eds., American Mathematical Society, Providence, RI, 2010, pp. 239–259]. In this paper, we investigate the effectiveness of combining a fixed number of Gaussian graphical models respecting some consistency assumptions in problems of model building. In particular, we use the meta-Markov combination of Gaussian graphical models as detailed in Massa and Lauritzen and compare model selection results obtained by combining selections over smaller sets of variables with selection results over all variables of interest. In order to do so, we carry out some simulation studies in which different criteria are considered for the selection procedures. We conclude that the combination performs, generally, better than global estimation, is computationally simpler by virtue of having fewer and simpler models to work on, and has an intuitive appeal to a wide variety of contexts.     

Hofstede's I-C Dimension as Predictive of Allocative Behaviors: A Meta-Analysis

There is a growing consensus in the scholarly and practitioner literature that theories of management do not always translate simply and universally. Using meta-analytic techniques, we explore Hofstede’s (1980) prediction that aculture’s score on individualism-collectivism will be associated with a normative preference for certain distributive justice principles. Findings indicate that in individualistic countries the preference favors the equity rule over equality or need in reward allocation. Conversely, in relatively collectivistic societies equality or need is emphasized. Moreover, in collectivistic societies the equity rule appears to be preferred with out-group members and equality or need with-in group. This revised version was published online in July 2006 with corrections to the Cover Date.     

Fisher information in weighted distributions

Suppose that a density f_θ (x) belongs to an exponential family, but that inference about θ must be based on data that are obtained from a density that is proportional to W(x)f_θ(x). The authors study the Fisher information about θ in observations obtained from such weighted distributions and give conditions under which this information is greater than under the original density. These conditions involve the hazard- and reversed-hazard-rate functions.     

Cognitive behavioral interventions for depression among Hispanic people: promising meta-analytic evidence for deep cultural adaptations

ABSTRACT

Depressive disorders are common among Hispanic people. Evidence-informed guidelines indicate cognitive behavioral interventions (CBI), but they were developed primarily with non-Hispanic White people. Narrative studies of clients and workers along systematic review evidence suggested that well-defines cultural adaptations of CBIs would likely improve outcomes among Hispanics people with diverse mental health problems. We advanced the meta-analytic hypothesis that CBIs incorporating so-called “deep structure” cultural adaptations will be more effective than otherwise similar, but more superficially, “surface structure” or non-adapted interventions with depressed Hispanic people. This meta-analysis synthesized evidence from nine typically randomized trials in the United States with one subsample from the Commonwealth of Puerto Rico. Most clients were young women, living in poverty and suffering a reactive depressive episode. We found statistical and practical support for our hypothesis. In most practice contexts, CBI success rates were between 15% and 30% better than those typically observed with other usual practices. Moreover, these effects were maintained at 6- to 12-month follow-up. Given the size and growth of the Hispanic American population, their prevalent experience of depression, and the size of the intervention effects, these synthesized findings seem of potentially great human, clinical, and policy significance.     

军人症状自评量表测评的元分析

目的:整合军人症状自评测验的研究结果,探索普遍性结论。方法:通过中国期刊网搜索以SCL-90为工具对军人的调查研究报告,进行元分析。结果:以全国常模为对照组,平均效应值都大于0但较低,以军人常模为对照组,平均效应量都为负值,说明全国常模可能由于年代的原因略偏低、军人常模偏高;军人的精神病性因子分较高。结论:症状自评量表在我国被非常广泛地应用于正常人群,但仍存许多问题需要研究和规范。     

A meta-analytic framework to adjust for bias in external control studies

While randomized controlled trials (RCTs) are the gold standard for estimating treatment effects in medical research, there is increasing use of and interest in using real-world data for drug development. One such use case is the construction of external control arms for evaluation of efficacy in single-arm trials, particularly in cases where randomization is either infeasible or unethical. However, it is well known that treated patients in non-randomized studies may not be comparable to control patients—on either measured or unmeasured variables—and that the underlying population differences between the two groups may result in biased treatment effect estimates as well as increased variability in estimation. To address these challenges for analyses of time-to-event outcomes, we developed a meta-analytic framework that uses historical reference studies to adjust a log hazard ratio estimate in a new external control study for its additional bias and variability. The set of historical studies is formed by constructing external control arms for historical RCTs, and a meta-analysis compares the trial controls to the external control arms. Importantly, a prospective external control study can be performed independently of the meta-analysis using standard causal inference techniques for observational data. We illustrate our approach with a simulation study and an empirical example based on reference studies for advanced non-small cell lung cancer. In our empirical analysis, external control patients had lower survival than trial controls (hazard ratio: 0.907), but our methodology is able to correct for this bias. An implementation of our approach is available in the R package ecmeta .