Nonparametric estimation of the random effects distribution for the risk or rate ratio in rare events meta-analysis with the arm-based and contrast-based approaches.

Rare events are events which occur with low frequencies. These often arise in clinical trials or cohort studies where the data are arranged in binary contingency tables. In this article, we investigate the estimation of effect heterogeneity for the risk-ratio parameter in meta-analysis of rare events studies through two likelihood-based nonparametric mixture approaches: an arm-based and a contrast-based model.

Rare events meta-analysis using the Bayesian beta-binomial model.

In meta-analyses of rare events, it can be challenging to obtain a reliable estimate of the pooled effect, in particular when the meta-analysis is based on a small number of studies. Recent simulation studies have shown that the beta-binomial model is a promising candidate in this situation, but have thus far only investigated its performance in a frequentist framework. In this study, we aim to make the beta-binomial model for meta-analysis of rare events amenable to Bayesian inference by proposing prior distributions for the effect parameter and investigating the models' robustness to different specifications of priors for the scale parameter.

The Manic Idea Creator? A Review and Meta-Analysis of the Relationship between Bipolar Disorder and Creative Cognitive Potential.

Even though a relationship between psychopathology and creativity has been postulated since the time of ancient Greece, systematic meta-analyses on this topic are still scarce. Thus, the meta-analysis described here can be considered the first to date that specifically focuses on the relationship between creative potential, as measured by divergent thinking, and bipolar disorder, as opposed to psychopathology in general. An extensive literature search of 4670 screened hits identified 13 suitable studies, including a total of 42 effect sizes and 1857 participants.

The efficacy and acceptability of psychological interventions for adult PTSD: A network and pairwise meta-analysis of randomized controlled trials.

Objective: A comprehensive quantitative summary of the efficacy and acceptability of psychological interventions (PIs) for adult posttraumatic stress disorder (PTSD) is lacking.

Method: We conducted a systematic literature search to identify randomized controlled trials (RCTs) examining the efficacy and acceptability (all-cause dropout) of psychological interventions (i.e.

ICAOD: An R Package for Finding Optimal designs for Nonlinear Statistical Models by Imperialist Competitive Algorithm.

Optimal design ideas are increasingly used in different disciplines to rein in experimental costs. Given a nonlinear statistical model and a design criterion, optimal designs determine the number of experimental points to observe the responses, the design points and the number of replications at each design point. Currently, there are very few free and effective computing tools for finding different types of optimal designs for a general nonlinear model, especially when the criterion is not differentiable.

Estimating risk and rate ratio in rare events meta-analysis with the Mantel-Haenszel estimator and assessing heterogeneity.

Meta-analysis of binary outcome data faces often a situation where studies with a rare event are part of the set of studies to be considered. These studies have low occurrence of event counts to the extreme that no events occur in one or both groups to be compared. This raises issues how to estimate validly the summary risk or rate ratio across studies.

Random-effects meta-analysis models for the odds ratio in the case of rare events under different data-generating models: A simulation study.

Meta-analysis of binary data is challenging when the event under investigation is rare, and standard models for random-effects meta-analysis perform poorly in such settings. In this simulation study, we investigate the performance of different random-effects meta-analysis models in terms of point and interval estimation of the pooled log odds ratio in rare events meta-analysis. First and foremost, we evaluate the performance of a hypergeometric-normal model from the family of generalized linear mixed models (GLMMs), which has been recommended, but has not yet been thoroughly investigated for rare events meta-analysis.

The relationship of trauma-related guilt with PTSD symptoms in adult trauma survivors: a meta-analysis.

Posttraumatic stress disorder (PTSD) is a severe condition that is associated with trauma-related guilt. We aimed at providing a comprehensive quantitative systematic review on the relationship between trauma-related guilt and adult PTSD. Database searches in Medline, PsycINFO, PTSDpubs and Web of Knowledge resulted in the inclusion of 163 eligible studies with a total of 35 020 trauma survivors.

Estimation of Effect Heterogeneity in Rare Events Meta-Analysis.

The paper outlines several approaches for dealing with meta-analyses of count outcome data. These counts are the accumulation of occurred events, and these events might be rare, so a special feature of the meta-analysis is dealing with low counts including zero-count studies. Emphasis is put on approaches which are state of the art for count data modelling including mixed log-linear (Poisson) and mixed logistic (binomial) regression as well as nonparametric mixture models for count data of Poisson and binomial type.

Neurology and neuropsychiatry of COVID-19: a systematic review and meta-analysis of the early literature reveals frequent CNS manifestations and key emerging narratives.

There is accumulating evidence of the neurological and neuropsychiatric features of infection with SARS-CoV-2. In this systematic review and meta-analysis, we aimed to describe the characteristics of the early literature and estimate point prevalences for neurological and neuropsychiatric manifestations.We searched MEDLINE, Embase, PsycINFO and CINAHL up to 18 July 2020 for randomised controlled trials, cohort studies, case-control studies, cross-sectional studies and case series.

The Relationship between Intelligence and Divergent Thinking-A Meta-Analytic Update.

This paper provides a meta-analytic update on the relationship between intelligence and divergent thinking (DT), as research on this topic has increased, and methods have diversified since Kim's meta-analysis in 2005. A three-level meta-analysis was used to analyze 849 correlation coefficients from 112 studies with an overall = 34,610. The overall effect showed a significant positive correlation of = .

Can High-Dimensional Questionnaires Resolve the Ipsativity Issue of Forced-Choice Response Formats?

Forced-choice questionnaires can prevent faking and other response biases typically associated with rating scales. However, the derived trait scores are often unreliable and ipsative, making interindividual comparisons in high-stakes situations impossible. Several studies suggest that these problems vanish if the number of measured traits is high.

An Experimental Approach to Investigate the Involvement of Cognitive Load in Divergent Thinking.

Up to now, support for the idea that a controlled component exists in creative thought has mainly been supported by correlational studies; to further shed light on this issue, we employed an experimental approach. We used four alternate uses tasks that differed in instruction type ("be fluent" vs. "be creative") and concurrent secondary workload (load vs.

Blood-Based ATN Biomarkers of Alzheimer's Disease: A Meta-Analysis.

Background: The Amyloid Tau Neurodegeneration (ATN) framework was proposed to define the biological state underpinning Alzheimer's disease (AD). Blood-based biomarkers offer a scalable alternative to the costly and invasive currently available biomarkers.

Objective: In this meta-analysis we sought to assess the diagnostic performance of plasma amyloid (Aβ40, Aβ42, Aβ42/40 ratio), tangle (p-tau181), and neurodegeneration (total tau [t-tau], neurofilament light [NfL]) biomarkers.

Introducing a Computerized Figural Memory Test Based on Automatic Item Generation: An Analysis With the Rasch Poisson Counts Model.

An automatic item generator for figural memory test items called was developed. It is available in . A cognitive model allowed the generation of hypothetically parallel items within three difficulty levels determined by visual information load.

Estimating the undetected infections in the Covid-19 outbreak by harnessing capture-recapture methods.

Objectives: A major open question, affecting the decisions of policy makers, is the estimation of the true number of Covid-19 infections. Most of them are undetected, because of a large number of asymptomatic cases. We provide an efficient, easy to compute and robust lower bound estimator for the number of undetected cases.

Comparison of random-effects meta-analysis models for the relative risk in the case of rare events: A simulation study.

Pooling the relative risk (RR) across studies investigating rare events, for example, adverse events, via meta-analytical methods still presents a challenge to researchers. The main reason for this is the high probability of observing no events in treatment or control group or both, resulting in an undefined log RR (the basis of standard meta-analysis). Other technical challenges ensue, for example, the violation of normality assumptions, or bias due to exclusion of studies and application of continuity corrections, leading to poor performance of standard approaches.

Disease-modifying treatments and cognition in relapsing-remitting multiple sclerosis: A meta-analysis.

Objective: Disease-modifying treatments (DMTs) are the gold standard for slowing disability progression in multiple sclerosis (MS), but their effects on cognitive impairment, a key symptom of the disease, are mostly unknown. We conducted a systematic review and meta-analysis to evaluate the differential effects of DMTs on cognitive test performance in relapsing-remitting MS (RRMS).

Methods: PubMed, Scopus, and Cochrane Library were searched for studies reporting longitudinal cognitive performance data related to all major DMTs.

D-optimal design for the Rasch counts model with multiple binary predictors.

In this paper we derive optimal designs for the Rasch Poisson counts model and its extended version of the (generalized) negative binomial counts model incorporating several binary predictors for the difficulty parameter. To efficiently estimate the regression coefficients of the predictors, locally D-optimal designs are developed. After an introduction to the Rasch Poisson counts model and its extension, we will specify these models as particular generalized linear models.

Psychological interventions for posttraumatic stress disorder and depression in refugees: A meta-analysis of randomized controlled trials.

Millions of refugees around the globe suffer from posttraumatic stress disorder (PTSD) and/or depression. We conducted a meta-analysis of randomized controlled trials (RCTs) to determine the efficacy of psychological interventions for PTSD and/or depression in refugees. The meta-analysis was registered on the PROSPERO database (CRD42017071384).

Scrutinizing the basis of originality in divergent thinking tests: On the measurement precision of response propensity estimates.

Background: The originality of divergent thinking (DT) production is one of the most critical indicators of creative potential. It is commonly scored using the statistical infrequency of responses relative to all responses provided in a given sample.

Aims: Response frequency estimates vary in terms of measurement precision.

The Impact of Situational Test Anxiety on Retest Effects in Cognitive Ability Testing: A Structural Equation Modeling Approach.

When a cognitive ability is assessed repeatedly, test scores and ability estimates are often observed to increase across test sessions. This phenomenon is known as the retest (or practice) effect. One explanation for retest effects is that situational test anxiety interferes with a testee's performance during earlier test sessions, thereby creating systematic measurement bias on the test items (interference hypothesis).

On the Statistical and Practical Limitations of Thurstonian IRT Models.

Forced-choice questionnaires have been proposed to avoid common response biases typically associated with rating scale questionnaires. To overcome ipsativity issues of trait scores obtained from classical scoring approaches of forced-choice items, advanced methods from item response theory (IRT) such as the Thurstonian IRT model have been proposed. For convenient model specification, we introduce the thurstonianIRT R package, which uses Mplus, lavaan, and Stan for model estimation.

Confining the Concept of Vascular Depression to Late-Onset Depression: A Meta-Analysis of MRI-Defined Hyperintensity Burden in Major Depressive Disorder and Bipolar Disorder.

The emphasizes the significance of vascular lesions in late-life depression. At present, no meta-analytic model has investigated whether a difference in hyperintensity burden compared to controls between late-life and late-onset depression is evident. By including a substantial number of studies, focusing on a meaningful outcome measure, and considering several moderating and control variables, the present meta-analysis investigates the severity of hyperintensity burden in major depressive disorder (MDD) and bipolar disorder (BD).