His main research concerns Meta-analysis, Econometrics, Systematic review, Statistics and Meta-Analysis as Topic. His research integrates issues of Placebo and Applied psychology in his study of Meta-analysis. His research in Econometrics intersects with topics in Statistical hypothesis testing, Statistic, Study heterogeneity and Random effects model.
As a part of the same scientific family, Julian P T Higgins mostly works in the field of Study heterogeneity, focusing on Funnel plot and, on occasion, Selection bias, Forest plot and Null hypothesis. His Systematic review study combines topics in areas such as Psychological intervention, Confounding, Research design and Risk analysis. His Meta-Analysis as Topic research integrates issues from Medical physics, Randomized controlled trial and Artificial intelligence.
Julian P T Higgins mostly deals with Meta-analysis, Systematic review, Econometrics, Statistics and Randomized controlled trial. His Meta-analysis research focuses on subjects like Psychological intervention, which are linked to Clinical trial. The study incorporates disciplines such as Research design, Observational study, Data science and Family medicine in addition to Systematic review.
His Econometrics research incorporates elements of Study heterogeneity, Statistic and Bayesian probability, Bayes' theorem. His Bayes' theorem research includes elements of Prior probability and Data mining. His Internal medicine study integrates concerns from other disciplines, such as Surgery, Oncology and Cardiology.
Meta-analysis, Psychological intervention, Systematic review, Randomized controlled trial and Statistics are his primary areas of study. His study in Meta-analysis is interdisciplinary in nature, drawing from both Odds ratio, Econometrics, Confidence interval, Intervention effect and Blinding. Julian P T Higgins has included themes like Empirical evidence, Publication bias and Inverse-variance weighting in his Econometrics study.
His Psychological intervention research is multidisciplinary, relying on both Research design, Credibility, Clinical trial and Alternative medicine. Julian P T Higgins has researched Systematic review in several fields, including Data science, Risk analysis, Confounding and Medical education. His study focuses on the intersection of Statistics and fields such as Random effects model with connections in the field of Inference.
His scientific interests lie mostly in Meta-analysis, Medical physics, Systematic review, Psychological intervention and Randomized controlled trial. His Meta-analysis study incorporates themes from Odds ratio, Social psychology, Econometrics, Confidence interval and Child mortality. Julian P T Higgins frequently studies issues relating to Inverse-variance weighting and Econometrics.
As part of the same scientific family, Julian P T Higgins usually focuses on Confidence interval, concentrating on Random effects model and intersecting with Statistics. His Medical physics research is multidisciplinary, incorporating perspectives in Intervention, Certainty and Research design. Julian P T Higgins combines subjects such as Health technology, Nursing, Medical education, Alternative medicine and Clinical psychology with his study of Systematic review.
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Cochrane Handbook for Systematic Reviews of Interventions
Julian P. T. Higgins;Sally Green.
Measuring inconsistency in meta-analyses
Julian P T Higgins;Simon G Thompson;Jonathan J Deeks;Douglas G Altman.
Assessing Risk of Bias in Included Studies
Julian Pt Higgins;Douglas G Altman.
Quantifying heterogeneity in a meta‐analysis
Julian P. T. Higgins;Simon G. Thompson.
Statistics in Medicine (2002)
The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials
Julian P T Higgins;Douglas G Altman;Peter C Gøtzsche;Peter Jüni.
Introduction to Meta-Analysis
Michael Borenstein;Larry V. Hedges;Julian P. T. Higgins;Hannah R. Rothstein.
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
D Moher;A Liberati;J Tetzlaff;D G Altman.
Revista Española de Nutrición Humana y Dietética (2014)
Cochrane Handbook for Systematic Reviews of Interventions, Version 5.1.0. The Cochrane Collaboration
Jpt Higgins;S. R. Green;J Higgins.
ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions.
Jonathan A. C. Sterne;Miguel A Hernan;Barnaby C Reeves;Jelena Savovic;Jelena Savovic.
Chapter 8: Assessing risk of bias in included studies
J P Higgins;D G Altman.
Cochrane handbook for systematic reviews of interventions (2008)
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