Research Cycles: Adding More Substance to the Spin

2016 ◽  
Vol 14 (4) ◽  
pp. 1067-1070 ◽  
Author(s):  
Colin Elman ◽  
Colleen Dougherty Burton
Keyword(s):  
Causal Inference ◽  
Randomized Controlled Trials ◽  
Political Science ◽  
Biomedical Research ◽  
Controlled Trials ◽  
Natural Experiments ◽  
Journal Editors ◽  
Randomized Controlled ◽  
Research Activities ◽  
Research Cycle

In sciences such as biomedicine, researchers and journal editors are well aware that progress in answering difficult questions generally requires movement through a research cycle: Research on a topic or problem progresses from pure description, through correlational analyses and natural experiments, to phased randomized controlled trials (RCTs). In biomedical research all of these research activities are valued and find publication outlets in major journals. In political science, however, a growing emphasis on valid causal inference has led to the suppression of work early in the research cycle. The result of a potentially myopic emphasis on just one aspect of the cycle reduces incentives for discovery of new types of political phenomena, and more careful, efficient, transparent, and ethical research practices. Political science should recognize the significance of the research cycle and develop distinct criteria to evaluate work at each of its stages.

scholarly journals Can the Biomedical Research Cycle be a Model for Political Science?

2016 ◽  
Vol 14 (4) ◽  
pp. 1054-1066 ◽  
Author(s):  
Evan S. Lieberman
Keyword(s):  
Causal Inference ◽  
Randomized Controlled Trials ◽  
Political Science ◽  
Biomedical Research ◽  
Controlled Trials ◽  
Natural Experiments ◽  
Journal Editors ◽  
Randomized Controlled ◽  
Research Activities ◽  
Research Cycle

In sciences such as biomedicine, researchers and journal editors are well aware that progress in answering difficult questions generally requires movement through a research cycle: Research on a topic or problem progresses from pure description, through correlational analyses and natural experiments, to phased randomized controlled trials (RCTs). In biomedical research all of these research activities are valued and find publication outlets in major journals. In political science, however, a growing emphasis on valid causal inference has led to the suppression of work early in the research cycle. The result of a potentially myopic emphasis on just one aspect of the cycle reduces incentives for discovery of new types of political phenomena, and more careful, efficient, transparent, and ethical research practices. Political science should recognize the significance of the research cycle and develop distinct criteria to evaluate work at each of its stages.

scholarly journals Best (but oft-forgotten) practices: missing data methods in randomized controlled nutrition trials

2019 ◽  
Vol 109 (3) ◽  
pp. 504-508 ◽  
Author(s):  
Peng Li ◽  
Elizabeth A Stuart
Keyword(s):  
Missing Data ◽  
Maximum Likelihood ◽  
Causal Inference ◽  
Randomized Controlled Trials ◽  
Multiple Imputation ◽  
Controlled Trials ◽  
Full Information ◽  
Complete Case ◽  
Full Information Maximum Likelihood ◽  
Randomized Controlled

ABSTRACT Missing data ubiquitously occur in randomized controlled trials and may compromise the causal inference if inappropriately handled. Some problematic missing data methods such as complete case (CC) analysis and last-observation-carried-forward (LOCF) are unfortunately still common in nutrition trials. This situation is partially caused by investigator confusion on missing data assumptions for different methods. In this statistical guidance, we provide a brief introduction of missing data mechanisms and the unreasonable assumptions that underlie CC and LOCF and recommend 2 appropriate missing data methods: multiple imputation and full information maximum likelihood.

Standards for reporting randomized controlled trials in neurosurgery

2011 ◽  
Vol 114 (2) ◽  
pp. 280-285 ◽  
Author(s):  
Erin N. Kiehna ◽  
Robert M. Starke ◽  
Nader Pouratian ◽  
Aaron S. Dumont
Keyword(s):  
New England ◽  
Randomized Controlled Trials ◽  
Controlled Trials ◽  
Jadad Score ◽  
Quality Of Reporting ◽  
Medical Journals ◽  
Journal Editors ◽  
Randomized Controlled ◽  
Neurosurgical Patients

Object The Consolidated Standards for Reporting of Trials (CONSORT) criteria were published in 1996 to standardize the reporting and improve the quality of clinical trials. Despite having been endorsed by major medical journals and shown to improve the quality of reported trials, neurosurgical journals have yet to formally adopt these reporting criteria. The purpose of this study is to evaluate the quality and reporting of randomized controlled trials (RCTs) in neurosurgery and the factors that may affect the quality of reported trials. Methods The authors evaluated all neurosurgical RCTs published in 2006 and 2007 in the principal neurosurgical journals (Journal of Neurosurgery; Neurosurgery; Surgical Neurology; Journal of Neurology, Neurosurgery, and Psychiatry; and Acta Neurochirurgica) and in 3 leading general medical journals (Journal of the American Medical Association, Lancet, and the New England Journal of Medicine). Randomized controlled trials that addressed operative decision making or the treatment of neurosurgical patients were included in this analysis. The RCT quality was evaluated using the Jadad score and the CONSORT checklist. Results In 2006 and 2007, 27 RCTs relevant to intracranial neurosurgery were reported. Of these trials, only 59% had a Jadad score ≥ 3. The 3 major medical journals all endorsed the CONSORT guidelines, while none of the neurosurgical journals have adopted these guidelines. Randomized controlled trials published in the 3 major medical journals had a significantly higher mean CONSORT score (mean 41, range 39–44) compared with those published in neurosurgical journals (mean 26.4, range 17–38; p < 0.0001). Jadad scores were also significantly higher for the major medical journals (mean 3.42, range 2–5) than neurosurgical journals (mean 2.45, range 1–5; p = 0.05). Conclusions Despite the growing volume of RCTs in neurosurgery, the quality of reporting of these trials remains suboptimal, especially in the neurosurgical journals. Improved awareness of the CONSORT guidelines by journal editors, reviewers, and authors of these papers could improve the methodology and reporting of RCTs in neurosurgery.

scholarly journals A survey of methodologies on causal inference methods in meta-analyses of randomized controlled trials

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Georgios Markozannes ◽  
Georgia Vourli ◽  
Evangelia Ntzani
Keyword(s):  
Causal Inference ◽  
Randomized Controlled Trials ◽  
Meta Analysis ◽  
Controlled Trials ◽  
Generation Process ◽  
Data Generation ◽  
Randomized Controlled ◽  
Data Generation Process ◽  
Meta Analyses ◽  
Inference Methods

Abstract Background Meta-analyses of randomized controlled trials (RCTs) have been considered as the highest level of evidence in the pyramid of the evidence-based medicine. However, the causal interpretation of such results is seldom studied. Methods We systematically searched for methodologies pertaining to the implementation of a causally explicit framework for meta-analysis of randomized controlled trials and discussed the interpretation and scientific relevance of such causal estimands. We performed a systematic search in four databases to identify relevant methodologies, supplemented with hand-search. We included methodologies that described causality under counterfactuals and potential outcomes framework. Results We only identified three efforts explicitly describing a causal framework on meta-analysis of RCTs. Two approaches required individual participant data, while for the last one, only summary data were required. All three approaches presented a sufficient framework under which a meta-analytical estimate is identifiable and estimable. However, several conceptual limitations remain, mainly in regard to the data generation process under which the selected RCTs rise. Conclusions We undertook a review of methodologies on causal inference methods in meta-analyses. Although all identified methodologies provide valid causal estimates, there are limitations in the assumptions regarding the data generation process and sampling of the potential RCTs to be included in the meta-analysis which pose challenges to the interpretation and scientific relevance of the identified causal effects. Despite both causal inference and meta-analysis being extensively studied in the literature, limited effort exists of combining those two frameworks.

1. Economics and behaviour

2017 ◽  
pp. 1-7
Author(s):  
Michelle Baddeley
Keyword(s):  
Decision Making ◽  
Randomized Controlled Trials ◽  
Evolutionary Biology ◽  
Reliable Data ◽  
Controlled Trials ◽  
Rational Decision ◽  
Natural Experiments ◽  
Randomized Controlled ◽  
Financial Behaviour ◽  
Analytical Power

Why is there so much interest in behavioural economics and how is it different? ‘Economics and behaviour’ explains how behavioural economists bring economics together with insights from other disciplines, such as psychology, sociology, neuroscience, and evolutionary biology. Using this multidisciplinary approach, behavioural economists enrich our understanding of economic and financial behaviour, without necessarily abandoning the analytical power often associated with conventional economics. Behavioural economists assume there are some limits to rational decision-making and draw on the concepts of bounded, ecological, and selective rationality. Behavioural economists also need to find relevant and reliable data including experimental and neuroscientific data. Natural experiments and randomized controlled trials are explained.

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