Conducting Meta-Analyses in R with the metafor Package

The metafor package provides functions for conducting meta-analyses in R. The package includes functions for fitting the meta-analytic fixed- and random-effects models and allows for the inclusion of moderators variables (study-level covariates) in these models. Meta-regression analyses with continuous and categorical moderators can be conducted in this way. Functions for the Mantel-Haenszel and Peto's one-step method for meta-analyses of 2 x 2 table data are also available. Finally, the package provides various plot functions (for example, for forest, funnel, and radial plots) and functions for assessing the model fit, for obtaining case diagnostics, and for tests of publication bias.

The meaning of adherence when behavioral risk patterns vary : obscured use- and method-effectiveness in HIV-prevention trials

Peer reviewedPublisher PD

Characterizing the Conductivity and Enhancing the Piezoresistivity of Carbon Nanotube-Polymeric Thin Films.

The concept of lightweight design is widely employed for designing and constructing aerospace structures that can sustain extreme loads while also being fuel-efficient. Popular lightweight materials such as aluminum alloy and fiber-reinforced polymers (FRPs) possess outstanding mechanical properties, but their structural integrity requires constant assessment to ensure structural safety. Next-generation structural health monitoring systems for aerospace structures should be lightweight and integrated with the structure itself. In this study, a multi-walled carbon nanotube (MWCNT)-based polymer paint was developed to detect distributed damage in lightweight structures. The thin film's electromechanical properties were characterized via cyclic loading tests. Moreover, the thin film's bulk conductivity was characterized by finite element modeling

Conducting Meta-Analyses in R with the metafor Package

The metafor package provides functions for conducting meta-analyses in R. The package includes functions for fitting the meta-analytic fixed- and random-effects models and allows for the inclusion of moderators variables (study-level covariates) in these models. Meta-regression analyses with continuous and categorical moderators can be conducted in this way. Functions for the Mantel-Haenszel and Peto's one-step method for meta-analyses of 2 x 2 table data are also available. Finally, the package provides various plot functions (for example, for forest, funnel, and radial plots) and functions for assessing the model fit, for obtaining case diagnostics, and for tests of publication bias

The poolr Package for Combining Independent and Dependent p Values

The poolr package provides an implementation of a variety of methods for pooling (i.e., combining) p values, including Fisher's method, Stouffer's method, the inverse chisquare method, the binomial test, the Bonferroni method, and Tippett's method. More importantly, the methods can be adjusted to account for dependence among the tests from which the p values have been derived assuming multivariate normality among the test statistics. All methods can be adjusted based on an estimate of the effective number of tests or by using an empirically-derived null distribution based on pseudo replicates that mimics a proper permutation test. For the Fisher, Stouffer, and inverse chi-square methods, the test statistics can also be directly generalized to account for dependence, leading to Brown's method, Strube's method, and the generalized inverse chi-square method. In this paper, we describe the various methods, discuss their implementation in the package, illustrate their use based on several examples, and compare the poolr package with several other packages that can be used to combine p values

Cost-effectiveness of a nurse-based intervention (AIMS) to improve adherence among HIV-infected patients : Design of a multi-centre randomised controlled trial

Peer reviewedPublisher PD

Evidence That Environmental and Genetic Risks for Psychotic Disorder May Operate by Impacting on Connections Between Core Symptoms of Perceptual Alteration and Delusional Ideation

Background: Relational models of psychopathology propose that symptoms are dynamically connected and hypothesize that genetic and environmental influences moderate the strength of these symptom connections. Previous findings suggest that the interplay between hallucinations and delusions may play a crucial role in the development of psychotic disorder. The current study examined whether the connection between hallucinations and delusions is impacted by proxy genetic and environmental risk factors. Methods: Hallucinations and delusions at baseline and at 3-year follow-up were assessed in a sample of 1054 healthy siblings and 918 parents of 1109 patients with psychosis, and in 589 healthy controls (no familial psychosis risk). Environmental factors assessed were cannabis use, childhood trauma, and urbanicity during childhood. Logistic regression analyses tested whether familial psychosis risk predicted increased risk of delusions, given presence of hallucinations. Moderating effects of environmental factors on the hallucination-delusion association were tested in a similar fashion, restricted to the control and sibling groups. Results: The risk of delusions, given hallucinations, was associated with proxy genetic risk: 53% in parents, 47% in siblings, and 36% in controls. The hallucination-delusion association was stronger in those reporting cannabis use (risk difference: 32%) and childhood trauma (risk difference: 15%) although not all associations were statistically conclusive (respectively: p = .037; p = .054). A directionally similar but nonsignificant effect was found for urb anicity during childhood (risk difference: 14%, p = .357). Conclusion: The strength of the connection between delusions and hallucinations is associated with familial and environmental risks for psychotic disorder, suggesting that specific symptom connections in the early psychosis psychopathology network are informative of underlying mechanisms