Julian P T Higgins

Datos Biográficos

ID6479206
NOMBREJulian P T Higgins
NOMBRESJulian P T
APELLIDOHiggins
FIRMAHIGGINS J P T
AFILIACIONESMRC Biostatistics Unit
ORCID0000-0002-8323-2514
VERIFICADOSí
TOTAL DE OBRAS27
TOTAL DE CITAS1
TOTAL COMO AUTOR26
TOTAL COMO EDITOR1
PRIMER AÑO DE PUBLICACIÓN1984
AÑO MÁS RECIENTE DE PUBLICACIÓN2022
ÍNDICE H1

  • Suicide and self-harm in low- and middle- income countries during the Covid-19 pandemic

    Open AccessDuleeka Knipe, Ann John et al.ARTICLEPLOS Global Public Health2022

    There is widespread concern over the potential impact of the COVID-19 pandemic on suicide and self-harm globally, particularly in low- and middle-income countries (LMIC) where the burden of these behaviours is greatest. We synthesised the evidence from the published literature on the impact of the pandemic on suicide and self-harm in LMIC. This review is nested within a living systematic review (PROSPERO ID CRD42020183326 ) that continuously iden…

  • Introduction to Meta‐Analysis

    Open AccessMichael Borenstein, Larry V Hedges et al.BOOKIntroduction to Meta-Analysis2021

  • Risk‐of‐bias VISualization (robvis)

    Open AccessLuke A McGuinness, Julian P T HigginsARTICLEResearch Synthesis Methods2021

    Despite a major increase in the range and number of software offerings now available to help researchers produce evidence syntheses, there is currently no generic tool for producing figures to display and explore the risk‐of‐bias assessments that routinely take place as part of systematic review. However, tools such as the R programming environment and Shiny (an R package for building interactive web apps) have made it straightforward to produce …

  • Cochrane Handbook for Systematic Reviews of Interventions

    Open AccessFarhad Shokraneh, Carol Lefebvre et al.BOOKCochrane Handbook for Systematic…2019

    The revised edition of the Handbook offers the only guide on how to conduct, report and maintain a Cochrane Review The second edition of The Cochrane Handbook for Systematic Reviews of Interventions contains essential guidance for preparing and maintaining Cochrane Reviews of the effects of health interventions. Designed to be an accessible resource, the Handbook will also be of interest to anyone undertaking systematic reviews of interventions o…

  • RoB 2

    Open AccessJonathan Sterne, Jelena Savović et al.ARTICLEBMJ2019

    Assessment of risk of bias is regarded as an essential component of a systematic review on the effects of an intervention. The most commonly used tool for randomised trials is the Cochrane risk-of-bias tool. We updated the tool to respond to developments in understanding how bias arises in randomised trials, and to address user feedback on and limitations of the original tool.

  • Analysing data and undertaking meta‐analyses

    Open AccessJonathan J Deeks, Julian P T Higgins et al.OTHERCochrane Handbook for Systematic…2019

    This chapter describes the principles and methods used to carry out a meta-analysis for a comparison of two interventions for the main types of data encountered. A very common and simple version of the meta-analysis procedure is commonly referred to as the inverse-variance method. This approach is implemented in its most basic form in RevMan, and is used behind the scenes in many meta-analyses of both dichotomous and continuous data. Results may …

  • Impact of drinking water, sanitation and handwashing with soap on childhood diarrhoeal disease

    Open AccessJennyfer Wolf, Paul R Hunter et al.ARTICLETropical Medicine & International…2018

  • Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder

    Open AccessAndrea Cipriani, Toshi A Furukawa et al.ARTICLEThe Lancet2018

  • Basics of meta‐analysis

    Open AccessMichael Borenstein, Julian P T Higgins et al.ARTICLEResearch Synthesis Methods2017

    When we speak about heterogeneity in a meta‐analysis, our intent is usually to understand the substantive implications of the heterogeneity. If an intervention yields a mean effect size of 50 points, we want to know if the effect size in different populations varies from 40 to 60, or from 10 to 90, because this speaks to the potential utility of the intervention. While there is a common belief that the I 2 statistic provides this information, it …

  • Methods to estimate the between‐study variance and its uncertainty in meta‐analysis

    Open AccessAreti Angeliki Veroniki, Dan Jackson et al.ARTICLEResearch Synthesis Methods2016

    Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study var…

  • Robis

    Open AccessPenny Whiting, Jelena Savović et al.ARTICLEJournal of Clinical Epidemiology2016

  • Robins-I

    Open AccessJonathan Sterne, Jonathan AC Sterne et al.ARTICLEBMJ2016

    Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that d…

  • Academic Freedom and the Humanities

    Open AccessJohn Higgins, Julian P T HigginsARTICLECritical Studies in Teaching and…2015Referencias: 1

    This article presents some of the current challenges facing academic freedom and the humanities in South Africa as well as across the world. It focuses first on the shifting fortunes of academic freedom in South Africa, contrasting the pride of place given to it in the pre-1994 social imaginary with its current undermining in higher education policy. It further examines how this undermining is related to a general trend in a global higher educati…

  • Systematic review

    Open AccessJennyfer Wolf, Annette Prüss‐Üstün et al.ARTICLETropical Medicine & International…2014

  • Systematic review

    Open AccessMatthew C Freeman, Meredith E Stocks et al.ARTICLETropical Medicine & International…2014

  • The Cochrane Collaboration's tool for assessing risk of bias in randomised trials

    Open AccessJulian P T Higgins, D G Altman et al.ARTICLEBMJ2011

    Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate

  • Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials

    Open AccessJonathan Sterne, J A C Sterne et al.ARTICLEBMJ2011

    Funnel plots, and tests for funnel plot asymmetry, have been widely used to examine bias in the results of meta-analyses. Funnel plot asymmetry should not be equated with publication bias, because it has a number of other possible causes. This article describes how to interpret funnel plot asymmetry, recommends appropriate tests, and explains the implications for choice of meta-analysis model

  • Interpretation of random effects meta-analyses

    Open AccessRichard D Riley, Julian P T Higgins et al.ARTICLEBMJ2011

    estimates of treatment effect from random effects meta-analysis give only the average effect across all studies. Inclusion of prediction intervals, which estimate the likely effect in an individual setting, could make it easier to apply the results to clinical practice

  • A basic introduction to fixed-effect and random-effects models for meta-analysis

    Open AccessMichael Borenstein, Larry V Hedges et al.ARTICLEResearch Synthesis Methods2010

    There are two popular statistical models for meta-analysis, the fixed-effect model and the random-effects model. The fact that these two models employ similar sets of formulas to compute statistics, and sometimes yield similar estimates for the various parameters, may lead people to believe that the models are interchangeable. In fact, though, the models represent fundamentally different assumptions about the data. The selection of the appropriat…

  • Introduction to Meta‐Analysis

    Open AccessMichael Borenstein, Larry V Hedges et al.BOOKIntroduction to Meta-Analysis2009

  • A Re-Evaluation of Random-Effects Meta-Analysis

    Open AccessJulian P T Higgins, Simon G Thompson et al.ARTICLEJournal of the Royal Statistical…2009

    Meta-analysis in the presence of unexplained heterogeneity is frequently undertaken by using a random-effects model, in which the effects underlying different studies are assumed to be drawn from a normal distribution. Here we discuss the justification and interpretation of such models, by addressing in turn the aims of estimation, prediction and hypothesis testing. A particular issue that we consider is the distinction between inference on the m…

  • Meta-Regression in Stata

    Open AccessRoger M Harbord, Roger Harbord et al.ARTICLEThe Stata Journal: Promoting…2008

    We present a revised version of the metareg command, which performs meta-analysis regression (meta-regression) on study-level summary data. The major revisions involve improvements to the estimation methods and the addition of an option to use a permutation test to estimate p-values, including an adjustment for multiple testing. We have also made additions to the output, added an option to produce a graph, and included support for the predict com…

  • Controlling the risk of spurious findings from meta‐regression

    Open AccessJulian P T Higgins, Simon G ThompsonARTICLEStatistics in Medicine2004

    Meta‐regression has become a commonly used tool for investigating whether study characteristics may explain heterogeneity of results among studies in a systematic review. However, such explorations of heterogeneity are prone to misleading false‐positive results. It is unclear how many covariates can reliably be investigated, and how this might depend on the number of studies, the extent of the heterogeneity and the relative weights awarded to the…

  • Measuring inconsistency in meta-analyses

    Open AccessJulian P T Higgins, Simon G Thompson et al.ARTICLEBMJ2003

    Cochrane Reviews have recently started including the quantity I2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice?

  • How should meta‐regression analyses be undertaken and interpreted?

    Open AccessSimon G Thompson, Julian P T HigginsARTICLEStatistics in Medicine2002

    Appropriate methods for meta‐regression applied to a set of clinical trials, and the limitations and pitfalls in interpretation, are insufficiently recognized. Here we summarize recent research focusing on these issues, and consider three published examples of meta‐regression in the light of this work. One principal methodological issue is that meta‐regression should be weighted to take account of both within‐trial variances of treatment effects …