scholarly journals The Design of Clustered Observational Studies in Education

AERA Open ◽  
2020 ◽  
Vol 6 (3) ◽  
pp. 233285842095440
Author(s):  
Lindsay C. Page ◽  
Matthew A. Lenard ◽  
Luke Keele
Keyword(s):  
Best Practices ◽  
Observational Studies ◽  
Regression Models ◽  
Summer School ◽  
Sensitivity Analyses ◽  
Educational Effectiveness ◽  
Statistical Adjustment ◽  
Counterfactual Model ◽  
Educational Effectiveness Research

Clustered observational studies (COSs) are a critical analytic tool for educational effectiveness research. We present a design framework for the development and critique of COSs. The framework is built on the counterfactual model for causal inference and promotes the concept of designing COSs that emulate the targeted randomized trial that would have been conducted were it feasible. We emphasize the key role of understanding the assignment mechanism to study design. We review methods for statistical adjustment and highlight a recently developed form of matching designed specifically for COSs. We review how regression models can be profitably combined with matching and note best practices for estimates of statistical uncertainty. Finally, we review how sensitivity analyses can determine whether conclusions are sensitive to bias from potential unobserved confounders. We demonstrate concepts with an evaluation of a summer school reading intervention in a large U.S. school district.

scholarly journals Causal Effects of Prenatal Exposure to PM2.5 on Child Development and the Role of Unobserved Confounding

2019 ◽  
Vol 16 (22) ◽  
pp. 4381 ◽  
Author(s):  
Viola Tozzi ◽  
Aitana Lertxundi ◽  
Jesus M. Ibarluzea ◽  
Michela Baccini
Keyword(s):  
Prenatal Exposure ◽  
Observational Studies ◽  
Causal Effect ◽  
Airborne Particles ◽  
Sensitivity Analyses ◽  
Implicit Assumption ◽  
Neuropsychological Development ◽  
High Concentrations ◽  
Unmeasured Confounders

Prenatal exposure to airborne particles is a potential risk factor for infant neuropsychological development. This issue is usually explored by regression analysis under the implicit assumption that all relevant confounders are accounted for. Our aim is to estimate the causal effect of prenatal exposure to high concentrations of airborne particles with a diameter < 2.5 µm (PM2.5) on children’s psychomotor and mental scores in a birth cohort from Gipuzkoa (Spain), and investigate the robustness of the results to possible unobserved confounding. We adopted the propensity score matching approach and performed sensitivity analyses comparing the actual effect estimates with those obtained after adjusting for unobserved confounders simulated to have different strengths. On average, mental and psychomotor scores decreased of −2.47 (90% CI: −7.22; 2.28) and −3.18 (90% CI: −7.61; 1.25) points when the prenatal exposure was ≥17 μg/m3 (median). These estimates were robust to the presence of unmeasured confounders having strength similar to that of the observed ones. The plausibility of having omitted a confounder strong enough to drive the estimates to zero was poor. The sensitivity analyses conferred solidity to our findings, despite the large sampling variability. This kind of sensitivity analysis should be routinely implemented in observational studies, especially in exploring new relationships.

scholarly journals Prognostic and therapeutic role of vitamin D in COVID-19: systematic review and meta-analysis

2021 ◽  
Author(s):  
Harsha Anuruddhika Dissanayake ◽  
Nipun Lakshitha de Silva ◽  
Manilka Sumanatilleke ◽  
Sawanawadu Dilantha Neomal de Silva ◽  
Kavinga Kalhari Kobawaka Gamage ◽  
...  
Keyword(s):  
Vitamin D ◽  
High Risk ◽  
Vitamin D Deficiency ◽  
Observational Studies ◽  
Meta Analysis ◽  
Severe Disease ◽  
Risk Of Bias ◽  
Sensitivity Analyses ◽  
Cochrane Library

Abstract Purpose Vitamin D deficiency/insufficiency may increase the susceptibility to COVID-19. We aimed to determine the association between vitamin D deficiency/insufficiency and susceptibility to COVID-19, its severity, mortality and role of vitamin D in its treatment. Methods We searched CINHAL, Cochrane library, EMBASE, PubMED, Scopus, and Web of Science up to 30.05.2021 for observational studies on association between vitamin D deficiency/insufficiency and susceptibility to COVID-19, severe disease and death among adults, and, randomized controlled trials (RCTs) comparing vitamin D treatment against standard care or placebo, in improving severity or mortality among adults with COVID-19. Risk of bias was assessed using Newcastle-Ottawa scale for observational studies and AUB-KQ1 Cochrane tool for RCTs. Study-level data were analyzed using RevMan 5.3 and R (v4∙1∙0). Heterogeneity was determined by I  2 and sources were explored through pre-specified sensitivity analyses, subgroup analyses and meta-regressions. Results Of 1877 search results, 76 studies satisfying eligibility criteria were included. Seventy-two observational studies were included in the meta-analysis (n=1976099). Vitamin D deficiency/insufficiency increased the odds of developing COVID-19 (OR 1∙46, 95% CI 1∙28–1∙65, p&lt;0∙0001, I  2=92%), severe disease (OR 1∙90, 95% CI 1∙52–2∙38, p&lt;0.0001, I  2=81%) and death (OR 2∙07, 95% CI 1∙28–3∙35, p=0.003, I  2=73%). 25-hydroxy vitamin D (25(OH)D) concentration were lower in individuals with COVID-19 compared to controls (mean difference [MD] -3∙85 ng/mL, 95% CI -5∙44,-2∙26, p=&lt;0.0001), in patients with severe COVID-19 compared to controls with non-severe COVID19 (MD -4∙84 ng/mL, 95% CI -7∙32,-2∙35, p=0∙0001) and in non-survivors compared to survivors (MD -4∙80 ng/mL, 95%-CI -7∙89,-1∙71, p=0∙002). The association between vitamin D deficiency/insufficiency and death was insignificant when studies with high risk of bias or studies reporting unadjusted effect estimates were excluded. Risk of bias and heterogeneity were high across all analyses. Discrepancies in timing of vitamin D testing, definitions of severe COVID-19 and vitamin D deficiency/insufficiency partly explained the heterogeneity. Four RCTs were widely heterogeneous precluding meta-analysis. Conclusion Multiple observational studies involving nearly two million adults suggest vitamin D deficiency/insufficiency increases susceptibility to COVID-19 and severe COVID-19, although with a high risk of bias and heterogeneity. Association with mortality was less robust. Heterogeneity in RCTs precluded their meta-analysis.

scholarly journals Influence of the month of birth on persistence of ADHD in prospective studies: protocol for an individual patient data meta-analysis

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e040952
Author(s):  
Corentin J Gosling ◽  
Charlotte Pinabiaux ◽  
Serge Caparos ◽  
Richard Delorme ◽  
Samuele Cortese
Keyword(s):  
Observational Studies ◽  
Individual Patient Data ◽  
Meta Analysis ◽  
Neurodevelopmental Disorder ◽  
Patient Data ◽  
Sensitivity Analyses ◽  
Month Of Birth ◽  
Study Results ◽  
Registration Number

IntroductionAttention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder with symptoms, especially the hyperactive ones, that tend to decrease in severity with age. Interestingly, children born just before the school-entry cut-off date (ie, the youngest pupils of a classroom) are at higher risk of being diagnosed with ADHD compared with children born just after the cut-off date. Noteworthy, this month-of-birth effect tends to disappear with increasing absolute age. Therefore, it is possible that young children erroneously diagnosed with ADHD due to their month of birth present a lower chance to have their diagnosis confirmed at a later age, artificially reinforcing the low persistence of ADHD across the lifespan. This protocol outlines an individual patient data (IPD) meta-analysis of prospective observational studies to explore the role of the month of birth in the low persistence of ADHD across the lifespan.Methods and analysisFive databases will be systematically searched in order to find prospective observational studies where the presence of ADHD is assessed both at baseline and at a follow-up of at least 4 years. We will use a two-stage IPD meta-analytic approach to estimate the role of the month of birth in the persistence of ADHD. Various sensitivity analyses will be performed to assess the robustness of the results.Ethics and disseminationNo additional data will be collected and no de-identified raw data will be used. Ethics approval is thus not required for the present study. Results of this IPD meta-analysis will be submitted for publication in a peer-reviewed journal.PROSPERO registration numberCRD42020212650

The Science of Wisdom in a Polarized World: Knowns and Unknowns

2020 ◽  
Author(s):  
Igor Grossmann ◽  
Nic M. Weststrate ◽  
Monika Ardelt ◽  
Justin Peter Brienza ◽  
Mengxi Dong ◽  
...  
Keyword(s):  
Individual Differences ◽  
Problem Solving ◽  
Best Practices ◽  
Cognitive Sciences ◽  
Methodological Challenges ◽  
The Common ◽  
Empirical Approaches ◽  
And Training ◽  
Contextual Differences

Interest in wisdom in the cognitive sciences, psychology, and education has been paralleled by conceptual confusions about its nature and assessment. To clarify these issues and promote consensus in the field, wisdom researchers met in Toronto in July of 2019, resolving disputes through discussion. Guided by a survey of scientists who study wisdom-related constructs, we established a common wisdom model, observing that empirical approaches to wisdom converge on the morally-grounded application of metacognition to reasoning and problem-solving. After outlining the function of relevant metacognitive and moral processes, we critically evaluate existing empirical approaches to measurement and offer recommendations for best practices. In the subsequent sections, we use the common wisdom model to selectively review evidence about the role of individual differences for development and manifestation of wisdom, approaches to wisdom development and training, as well as cultural, subcultural, and social-contextual differences. We conclude by discussing wisdom’s conceptual overlap with a host of other constructs and outline unresolved conceptual and methodological challenges.

Beyond Bias

2020 ◽  
pp. 736-753
Author(s):  
Chelsea Barabas
Keyword(s):  
Best Practices ◽  
Criminal Law ◽  
Criminal Justice Reform ◽  
Trade Offs ◽  
System P ◽  
Accuracy Measures ◽  
Criminal Legal System ◽  
And Function ◽  
Role And Function

This chapter discusses contemporary debates regarding the use of artificial intelligence as a vehicle for criminal justice reform. It closely examines two general approaches to what has been widely branded as “algorithmic fairness” in criminal law: the development of formal fairness criteria and accuracy measures that illustrate the trade-offs of different algorithmic interventions; and the development of “best practices” and managerialist standards for maintaining a baseline of accuracy, transparency, and validity in these systems. Attempts to render AI-branded tools more accurate by addressing narrow notions of bias miss the deeper methodological and epistemological issues regarding the fairness of these tools. The key question is whether predictive tools reflect and reinforce punitive practices that drive disparate outcomes, and how data regimes interact with the penal ideology to naturalize these practices. The chapter then calls for a radically different understanding of the role and function of the carceral state, as a starting place for re-imagining the role of “AI” as a transformative force in the criminal legal system.

scholarly journals Long-term exposure to iron and copper in fine particulate air pollution and their combined impact on reactive oxygen species concentration in lung fluid: a population-based cohort study of cardiovascular disease incidence and mortality in Toronto, Canada

2020 ◽  
Author(s):  
Zilong Zhang ◽  
Scott Weichenthal ◽  
Jeffrey C Kwong ◽  
Richard T Burnett ◽  
Marianne Hatzopoulou ◽  
...  
Keyword(s):  
Reactive Oxygen Species ◽  
Cardiovascular Disease ◽  
Regression Models ◽  
Population Based ◽  
Sensitivity Analyses ◽  
Oxygen Species ◽  
Lung Fluid ◽  
Fine Particulate ◽  
Combined Impact

Abstract Background Exposure to fine particulate (PM2.5) air pollution is associated with increased cardiovascular disease (CVD), but less is known about its specific components, such as metals originating from non-tailpipe emissions. We investigated the associations of long-term exposure to metal components [iron (Fe) and copper (Cu)] in PM2.5 with CVD incidence. Methods We conducted a population-based cohort study in Toronto, Canada. Exposures to Fe and Cu in PM2.5 and their combined impact on the concentration of reactive oxygen species (ROS) in lung fluid were estimated using land use regression models. Incidence of acute myocardial infarction (AMI), congestive heart failure (CHF) and CVD death was ascertained using health administrative datasets. We used mixed-effects Cox regression models to examine the associations between the exposures and health outcomes. A series of sensitivity analyses were conducted, including indirect adjustment for individual-level cardiovascular risk factors (e.g. smoking), and adjustment for PM2.5 and nitrogen dioxide (NO2). Results In single-pollutant models, we found positive associations between the three exposures and all three outcomes, with the strongest associations detected for the estimated ROS. The associations of AMI and CHF were sensitive to indirect adjustment, but remained robust for CVD death in all sensitivity analyses. In multi-pollutant models, the associations of the three exposures generally remained unaltered. Interestingly, adjustment for ROS did not substantially change the associations between PM2.5 and CVD, but attenuated the associations of NO2. Conclusions Long-term exposure to Fe and Cu in PM2.5 and their combined impact on ROS were consistently associated with increased CVD death.

Curriculum in Cardiology To Adjust or Not to Adjust: The Role of Different Covariates in Cardiovascular Observational Studies

2021 ◽  
Author(s):  
Mahyar Etminan ◽  
James M. Brophy ◽  
Gary Collins ◽  
Maryam Nazemipour ◽  
Mohammad Ali Mansournia
Keyword(s):  
Observational Studies

scholarly journals Systemic Innovation Areas for Heritage-Led Rural Regeneration: A Multilevel Repository of Best Practices

2021 ◽  
Vol 13 (9) ◽  
pp. 5069
Author(s):  
Aitziber Egusquiza ◽  
Mikel Zubiaga ◽  
Alessandra Gandini ◽  
Claudia de Luca ◽  
Simona Tondelli
Keyword(s):  
Best Practices ◽  
Environmental Sustainability ◽  
Rural Areas ◽  
Role Models ◽  
Social Inclusion ◽  
Work Support ◽  
Community Capitals ◽  
Community Capitals Framework ◽  
Systemic Innovation

This paper presents the result of the analysis of the data gathered from 20 Role Models (RM) case studies regarding their successful heritage-led rural regeneration models. For the study and comparison of the narratives of these Role Models two tools were used: the Community Capitals Framework, which studied the transference of capitals in each process and the identification of six Systemic Innovation Areas that allow this capital transference. A multilevel repository of best practices has been developed allowing the identification of common features, mechanisms for mobilisation of capitals and required resources that will facilitate the replication in other rural areas. The results of this work support the acknowledgement of the contribution of culture, together with cultural and natural heritage, to economic growth, social inclusion and environmental sustainability in rural areas reinforcing the role of culture as the fourth pillar of sustainable development.

Role of Research in Best Practices

2015 ◽  
Vol 50 (1) ◽  
pp. 19-32 ◽  
Author(s):  
Maria A. Revell
Keyword(s):  
Best Practices
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