Accuracy and Precision of Fixed and Random Effects in Meta-Analyses of Randomized Control Trials for Continuous Outcomes

Meta-analyses of treatment effects in randomized control trials are often faced with the problem of missing information required to calculate effect sizes and their sampling variances. Particularly, correlations between pre- and posttest scores are frequently not available. As an ad-hoc solution, researchers impute a constant value for the missing correlation. As an alternative, we propose adopting a multivariate meta-regression approach that models independent group effect sizes and accounts for the dependency structure using robust variance estimation or three-level modeling. A comprehensive simulation study mimicking realistic conditions of meta-analyses in clinical and educational psychology suggested that the prevalent imputation approach works well for estimating the pooled effect but severely distorts the between-study heterogeneity. In contrast, the robust meta-regression approach resulted in largely unbiased fixed and random effects. Based on these results recommendations for meta-analytic practice and future meta-analytic developments are provided.

Catching Up on Multilevel Modeling

This review focuses on the use of multilevel models in psychology and other social sciences. We target readers who are catching up on current best practices and sources of controversy in the specification of multilevel models. We first describe common use cases for clustered, longitudinal, and cross-classified designs, as well as their combinations. Using examples from both clustered and longitudinal designs, we then address issues of centering for observed predictor variables: its use in creating interpretable fixed and random effects of predictors, its relationship to endogeneity problems (correlations between predictors and model error terms), and its translation into multivariate multilevel models (using latent-centering within multilevel structural equation models). Finally, we describe novel extensions—mixed-effects location–scale models—designed for predicting differential amounts of variability.

Testing the Green Bond Premium in COVID-19 Pandemia

The purpose of this chapter is testing the existence of the green bond premium in the secondary market by using a most update data set involving the market developments in the pandemia times. The variables such as rating, sector, amount of the issue, maturity, and external review are balanced by using a matching procedure of a green bond with conventional bond issued by the same issuer. The ask-bid spread differential is regressed by using a panel regression method under fixed and random effects. The results of the analysis revealed that there exists negative premium of 39 basis points, and the green bond premium is more profound for USD denominated twins than for Euro ones as there exist a negative premium of 59 basis points for USD-denominated green bonds whereas it is -26 basis points for Euro-denominated bonds.

Systematic Review and Meta-Analysis of L-Methylfolate Augmentation in Depressive Disorders

Objectives Partial response to pharmacotherapy is common in major depressive disorder (MDD) and many patients require alternative pharmacotherapy or augmentation, including adjunctive L-methylfolate. Given that L-methylfolate augmentation is rarely included in major clinical practice guidelines, we sought to systematically review evidence for L-methylfolate augmentation in adults with MDD and to examine its efficacy meta-analytically. Methods We systematically searched PubMed for articles up to December 31, 2020, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations. Included studies were published in peer-reviewed, English-language journals and examined L-methylfolate adjunctive therapy in depressive disorders or its effect on antidepressant response. A fixed- and random-effects meta-analysis and risk of bias assessment using the Cochrane Risk of Bias Tool were conducted. Results Qualitative assessment of nine articles (N=6,707 patients) suggests that adjunctive L-methylfolate improved antidepressant response. In the meta-analysis of categorical Hamilton Rating Scale for Depression-17 response, (three studies, N=483) adjunctive L-methylfolate was associated with a small effect versus antidepressant monotherapy (relative risk: 1.25, 95% confidence interval [CI]=1.08 to 1.46, p=0.004). A meta-analysis of four studies (N=507) using a continuous measure of depressive symptoms showed a similar effect of adjunctive L-methylfolate (standardized mean difference=− 0.38, 95% CI=− 0.59 to−0.17, p=0.0003). Conclusion Adjunctive L-methylfolate may have modest efficacy in antidepressant-treated adults with MDD.

Lateral versus vertical hemispheric disconnection for epilepsy: a systematic review and meta-analysis

OBJECTIVE Lateral periinsular hemispherotomy (LPH) and vertical parasagittal hemispherotomy (VPH) are the most popular disconnective techniques for intractable epilepsies associated with unilateral hemispheric pathologies. The authors aimed to investigate possible differences in seizure outcome and complication rates between patients who underwent LPH and VPH. METHODS A comprehensive literature search of PubMed and Embase identified English-language articles published from database inception to December 2019 that reported series (minimum 12 patients with follow-up ≥ 12 months) on either LPH or VPH. Pooled rates of seizure freedom and complications (with a particular focus on hydrocephalus) were analyzed using meta-analysis to calculate both fixed and random effects. Heterogeneity (Cochran’s Q test) and inconsistency (fraction of Q due to actual heterogeneity) were also calculated. RESULTS Twenty-five studies were included. Data from 825 patients were available for seizure outcome analysis (583 underwent LPH and 242 underwent VPH), and data from 692 patients were available for complication analysis (453 underwent LPH and 239 underwent VPH). No differences were found in the pooled rates of Engel class I seizure outcome between patients who underwent LPH (80.02% and 79.44% with fixed and random effects, respectively) and VPH (79.89% and 80.69% with fixed and random effects, respectively) (p = 0.953). No differences were observed in the pooled rates of shunted hydrocephalus between patients who underwent LPH (11.34% and 10.63% with fixed and random effects, respectively) and VPH (11.07% and 9.98% with fixed and random effects, respectively) (p = 0.898). Significant heterogeneity and moderate inconsistency were determined for hydrocephalus occurrence in patients who underwent both LPH and VPH. CONCLUSIONS LPH and VPH techniques present similar excellent seizure outcomes, with comparable and acceptable safety profiles.

Does income inequality matter for CO2 emissions in Russian regions?

Research background: Intensive economic growth in Russian regions during recent decades has been associated with numerous environmental issues, particularly increasing CO2 emissions, as well as income inequality. To achieve sustainable development, it is necessary to resolve these issues. Purpose of the article: To shed light on the impact of income inequality on CO2 emissions based on Russian regional data covering the years 2004?2018. Methods: Gini index and decile dispersion ratio are used to measure income inequality. To study the impact of income inequality on CO2 emissions in the Russian regions, we estimate econometric models with fixed and random effects and apply GMM method. We test the hypothesis of the environmental Kuznets curve to determine the impact of economic growth on CO2 emissions. Findings & value added: The results show that CO2 emissions increase in tandem with growth in income inequality between 10% of people with the lowest income and 10% of people with the highest income. Simultaneously, CO2 emissions decrease with growth of Gini coefficient. The hypothesis of the Environmental Kuznets Curve was confirmed based on GMM method. Our findings underscore that the activities of the extraction and manufacturing sectors, as well as energy consumption, increase CO2 emissions. The chief significance of this paper is the finding that large income gap between extremely rich and extremely poor population cohorts increases CO2 emissions. This implies that economic policy aimed at reducing income inequality in Russian regions will also reduce CO2 emissions, especially if accompanied by increased use of environmentally friendly technologies. From the international perspective, our research can be extended to study other countries and regions.

The Limits of Marginality

The “marginality principle” for linear regression models states that when a higher order term is included, its constituent terms must also be included. The target article relies on this principle for the fixed-effects part of linear mixed models of ANOVA designs and considers the implication that if extended to combined fixed-and-random-effects models, model selection tests specific to some fixed-effects ANOVA terms are not possible. We review the basis for this principle for fixed-effects models and delineate its limits. We then consider its extension to combined fixed-and-random-effects models. We conclude that we have been unable to find in the literature, including the target article, and have ourselves been unable to construct any satisfactory argument against the use of incomplete ANOVA models. The only basis we could find requires one to assume that it is not possible to test point-null hypotheses, something we disagree with, and which we believe is incompatible with the Bayesian model-selection methods that are the basis of the target article.

Money laundering, food activities and mafia: evidences from the Italian provinces

Purpose According to the INTERPOL definition, money laundering is: “any act or attempted act to conceal or disguise the identity of illegally obtained proceeds so that they appear to have originated from legitimate sources”. Along this line, the purpose of this paper is to investigate the link amongst money laundering, mafia and food activities, in the Italian provinces. Design/methodology/approach By using annual data over the period 2010 to 2018, the author estimates balanced panel data using the instrumental variables approach. The analysis includes both fixed and random effects, as well as robustness checks. Findings The main findings of this paper reveal that, in most Italian provinces, money launderers are deterred by the probability of being identified. In particular, the deterrent action of police and investigative forces seems to be very effective. Moreover, the results of the empirical analysis show that mafia-type organisations and food activities are positively correlated with money laundering. Originality/value This paper aims to provide a specific study on the link between apparently legal activities (food and beverage) and money laundering; a link that has so far been analysed mainly on a theoretical level. Moreover, it provides several insights in terms of policy implications.

Cost stickiness and firm profitability: A study in Saudi Arabian industries

This study examined the impact of cost stickiness on firm profitability in different industrial sectors in Saudi Arabia. The sample size for the study consists of 102 companies listed on Tadawul (Saudi Stock Exchange) from 2009 to 2018. The study estimated a panel regression using pooled OLS, fixed and random effects, and Generalized Method of Moments (GMM). The variable Return on Investment (ROI) is used as a proxy to measure a firm’s profitability. The results of all the three models are similar to each other. The study found a negative and significant correlation between profitability and cost stickiness, indicating firms’ inability to control the selling, general and administrative costs (SG&A), ultimately leading to lower profits. In addition, firm size is positively associated with profitability, indicating that larger firms are more profitable compared to smaller ones, while the leverage is negatively related to profitability, indicating that companies have higher debts.