James R Carpenter

Datos Biográficos

ID324893
NOMBREJames R Carpenter
NOMBRESJames R
APELLIDOCarpenter
FIRMACARPENTER J R
AFILIACIONESLondon School of Hygiene & Tropical Medicine
ORCID0000-0003-3890-6206
VERIFICADOSí
TOTAL DE OBRAS12
TOTAL DE CITAS6
TOTAL COMO AUTOR12
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN1969
AÑO MÁS RECIENTE DE PUBLICACIÓN2024
ÍNDICE H1

  • A Comparison of Three Popular Methods for Handling Missing Data

    Open AccessRoderick J Little, James R Carpenter et al.ARTICLESociological Methods & Research2024Citada por: 1Referencias: 35

    Missing data are a pervasive problem in data analysis. Three common methods for addressing the problem are (a) complete-case analysis, where only units that are complete on the variables in an analysis are included; (b) weighting, where the complete cases are weighted by the inverse of an estimate of the probability of being complete; and (c) multiple imputation (MI), where missing values of the variables in the analysis are imputed as draws from…

  • Variation in colon cancer survival for patients living and receiving care in London, 2006–2013

    Open AccessManuela Quaresma, James R Carpenter et al.ARTICLEJournal of Epidemiology and…2022Referencias: 17

    BACKGROUND: Marked geographical disparities in survival from colon cancer have been consistently described in England. Similar patterns have been observed within London, almost mimicking a microcosm of the country's survival patterns. This evidence has suggested that the area of residence plays an important role in the survival from cancer. METHODS: We analysed the survival from colon cancer of patients diagnosed in 2006-2013, in a pre-pandemic p…

  • Using automated voice messages linked to telephone counselling to increase post-menstrual regulation contraceptive uptake and continuation in Bangladesh

    Open AccessKate Reiss, Kathryn Andersen et al.ARTICLEBMC Public Health2017

    Trial registered with clinicaltrials.gov Registration number: NCT02579785 Date of registration: 16th October 2015

  • 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…

  • Meta-Analysis with R

    Open AccessGuido Schwarzer, James R Carpenter et al.BOOKMeta-Analysis with R2015

  • Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using Mice

    Open AccessAnoop D Shah, Jonathan Bartlett et al.ARTICLEAmerican Journal of Epidemiology2014

    Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The "true" imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be specified. We compared parametric MICE with a random…

  • The Moon

    Open AccessJames Nasmyth, James R Carpenter et al.BOOKMoon2013

    The movement of the moon in space had been well documented by the second half of the nineteenth century. In this monograph, which first appeared in 1874, James Nasmyth (1808–90) and James Carpenter (1840–99) pay closer attention to the lunar surface, notably illustrating their work with photographs of accurate plaster models. At this time, many questions about the moon's properties were still open. Could the moon support life? Did it have an atmo…

  • 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

  • Multiple imputation for missing data in epidemiological and clinical research

    Open AccessJonathan Sterne, J A C Sterne et al.ARTICLEBMJ2009

    Most studies have some missing data. Jonathan Sterne and colleagues describe the appropriate use and reporting of the multiple imputation approach to dealing with them

  • Shared Learning for Doctors and Social Workers

    James R Carpenter, J Carpenter et al.ARTICLEThe British Journal of Social Work1996Citada por: 1

    This paper reports a shared learning programme for final year social work and medical students which was designed in the light of social psychological studies of intergroup behaviour (the Contact Hypothesis). Key features included institutional support for the programme and opportunities to work as equals in pairs and small groups on shared tasks in a cooperative atmosphere. Topics included alcohol abuse, dealing with psychiatric emergencies, del…

  • Taro

    Joseph Arditti, James R Carpenter et al.BOOKTaro1983Citada por: 4

  • Roman Galley beneath the Sea

    James R Carpenter, James Carpenter et al.ARTICLEThe Classical World1969