Items where Author is "Carpenter, JR"
Up a level |
Number of items: 68.
Bibliographic data only
Brunton-Smith, I;
Carpenter, JR;
Kenward, MG;
Tarling, R;
(2014)
Multiple Imputation for handling missing data in social research.
Social Research Update, 65.
pp. 1-4.
http://sru.soc.surrey.ac.uk/
Full text not available from this repository.
Carpenter, J;
Plewis, I;
(2011)
Analysing longitudinal studies with non-response: issues and statistical methods.
In: Williams, M; Vogt, P, (eds.)
The SAGE handbook of Innovation in Social Research Methods.
Sage, New York, pp. 498-523.
http://researchonline.lshtm.ac.uk/id/eprint/179961
Full text not available from this repository.
Carpenter, J;
Pocock, S;
Lamm, CJ;
(2002)
Coping with missing data in clinical trials: a model-based approach applied to asthma trials.
Statistics in medicine, 21 (8).
pp. 1043-66.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.1065
Full text not available from this repository.
Carpenter, J;
Rücker, G;
Schwarzer, G;
(2008)
Comments on 'Fixed vs random effects meta-analysis in rare event studies: the rosiglitazone link with myocardial infarction and cardiac death'.
Statistics in medicine, 27 (19).
3910-2; author reply 3912-4.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.3173
Full text not available from this repository.
Carpenter, JR;
Kenward, MG;
(2016)
Sensitivity analysis with multiple imputation.
In: Molenberghs, G; Fitzmaurice, G; Kenward, MG; Tsiatis, A; Verbeke, G, (eds.)
Handbook of missing data methodology.
CRC press, Florida, pp. 435-470.
ISBN 978-1-4398-5461-7
http://researchonline.lshtm.ac.uk/id/eprint/2869423
Full text not available from this repository.
Carpenter, JR;
Kenward, MG;
(2015)
Developments of methods and critique of ad hoc methods.
In: Molenberghs, G; Fitzmaurice, G; Kenward, MG; Tsiatis, A; Verbeke, G, (eds.)
Handbook of missing data methodology.
CRC Press, Florida, pp. 23-46.
ISBN 978-1-4398-5461-7
http://researchonline.lshtm.ac.uk/id/eprint/2869428
Full text not available from this repository.
Carpenter, JR;
Roger, JH;
Cro, S;
Kenward, MG;
(2014)
Response to Comments by Seaman et al on Analysis of longitudinal trials with protocol deviation: a framework for relevant, accessible assumptions, and inference via multiple imputation, Journal of Biopharmaceutical Statistics, 23, 1352-1371.
Journal of biopharmaceutical statistics, 24 (6).
pp. 1363-9.
ISSN 1054-3406
DOI: https://doi.org/10.1080/10543406.2014.960085
Full text not available from this repository.
Chan, CW;
Carpenter, JR;
Rigamonti, C;
Gunsar, F;
Burroughs, AK;
(2004)
Survival following the development of ascites and/or oedema in primary biliary cirrhosis: A stage prognostic model.
[Conference or Workshop Item]
http://researchonline.lshtm.ac.uk/id/eprint/14702
Full text not available from this repository.
Cro, S;
Morris, TP;
Kenward, MG;
Carpenter, JR;
(2016)
Reference-based sensitivity analysis via multiple imputation for longitudinal trials with protocol deviation.
The Stata journal, 16 (2).
pp. 443-463.
ISSN 1536-867X
https://www.stata-journal.com/article.html?article...
Full text not available from this repository.
Driessen, J;
Williamson, E;
Carpenter, J;
de Vries, F;
(2016)
Evaluation of Different Missing Data Strategies in Propensity Score Analyses.
[Conference or Workshop Item]
http://researchonline.lshtm.ac.uk/id/eprint/3515668
Full text not available from this repository.
Falcaro, M;
Nur, U;
Rachet, B;
Carpenter, JR;
(2015)
Estimating Excess Hazard Ratios and Net Survival When Covariate Data Are Missing Strategies for Multiple Imputation.
Epidemiology (Cambridge, Mass), 26 (3).
pp. 421-428.
ISSN 1044-3983
DOI: https://doi.org/10.1097/EDE.0000000000000283
Full text not available from this repository.
Goldstein, H;
Carpenter, JR;
(2015)
Multilevel multiple imputation.
In: Molenberghs, G; Fitzmaurice, G; Kenward, MG; Tsiatis, A; Verbeke, G, (eds.)
Handbook of missing data methodology.
CRC press, Florida, pp. 295-376.
ISBN 978-1-4398-5461-7
http://researchonline.lshtm.ac.uk/id/eprint/2869420
Full text not available from this repository.
Goldstein, H;
Carpenter, JR;
Browne, WJ;
(2014)
Fitting multilevel multivariate models with missing data in responses and covariates that may include interactions and non-linear terms.
Journal of the Royal Statistical Society Series A, (Statistics in Society), 177 (2).
pp. 553-564.
ISSN 0964-1998
DOI: https://doi.org/10.1111/rssa.12022
Full text not available from this repository.
Gomes, M;
Grieve, R;
Nixon, R;
Ng, ES;
Carpenter, J;
Thompson, SG;
(2012)
METHODS FOR COVARIATE ADJUSTMENT IN COST-EFFECTIVENESS ANALYSIS THAT USE CLUSTER RANDOMISED TRIALS.
Health economics, 21 (9).
pp. 1101-18.
ISSN 1057-9230
DOI: https://doi.org/10.1002/hec.2812
Full text not available from this repository.
Hogan, JW;
Carpenter, J;
van Houwelingen, HC;
Sousa, I;
Didelez, V;
Cox, DR;
Aalen, OO;
Commenges, D;
Lawless, RCJ;
Hand, DJ;
+13 more...
Lin, HQ;
Lunn, M;
Martinussen, T;
Molenberghs, G;
Verbeke, G;
Pipper, CB;
Scheike, TH;
Scheike, TH;
Pipper, CB;
Solis-Trapala, IL;
Taylor, JMG;
Zeng, D;
Lin, DY;
(2007)
Discussion on the paper by Diggle, Farewell and Henderson.
Applied statistics, 56.
pp. 530-550.
ISSN 0035-9254
http://researchonline.lshtm.ac.uk/id/eprint/8472
Full text not available from this repository.
Kenward, MG;
White, IR;
Carpenter, JR;
(2010)
Should baseline be a covariate or dependent variable in analyses of change from baseline in clinical trials? by G. F. Liu, K. Lu, R. Mogg, M. Mallick and D. V. Mehrotra, Statistics in Medicine 2009; 28:2509-2530.
Statistics in medicine, 29 (13).
1455-6; author reply 1457.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.3868
Full text not available from this repository.
Morris, TP;
White, IR;
Carpenter, JR;
Stanworth, SJ;
Royston, P;
(2015)
Combining fractional polynomial model building with multiple imputation.
Statistics in medicine, 34 (25).
pp. 3298-317.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.6553
Full text not available from this repository.
Ng, ES;
Diaz-Ordaz, K;
Grieve, R;
Nixon, RM;
Thompson, SG;
Carpenter, JR;
(2013)
Multilevel models for cost-effectiveness analyses that use cluster randomised trial data: An approach to model choice.
Statistical methods in medical research.
ISSN 0962-2802
DOI: https://doi.org/10.1177/0962280213511719
Full text not available from this repository.
Ng, ESW;
Carpenter, JR;
Goldstein, H;
Rasbash, J;
(2006)
Estimation in generalised linear mixed models with binary outcomes by simulated maximum likelihood.
Statistical modelling, 6 (1).
pp. 23-42.
ISSN 1471-082X
DOI: https://doi.org/10.1191/1471082X06st106oa
Full text not available from this repository.
Ng, ESW;
Grieve, R;
Carpenter, JR;
(2013)
Two-stage nonparametric bootstrap sampling with shrinkage correction for clustered data.
The Stata journal, 13 (1).
pp. 141-164.
ISSN 1536-867X
http://www.stata-journal.com/article.html/?article...
Full text not available from this repository.
Parmar, MK;
Carpenter, J;
Sydes, MR;
(2014)
More multiarm randomised trials of superiority are needed.
Lancet, 384 (9940).
pp. 283-4.
ISSN 0140-6736
DOI: https://doi.org/10.1016/S0140-6736(14)61122-3
Full text not available from this repository.
Reeves, BC;
Langham, J;
Walker, J;
Grieve, R;
Chakravarthy, U;
Tomlin, K;
Carpenter, J;
Guerriero, C;
Harding, SP;
Verteporfin Photodynamic Therapy Cohort Study Group;
(2009)
Verteporfin photodynamic therapy cohort study report 2: clinical measures of vision and health-related quality of life.
Ophthalmology, 116 (12).
pp. 2463-70.
ISSN 0161-6420
DOI: https://doi.org/10.1016/j.ophtha.2009.10.031
Full text not available from this repository.
Schwarzer, G;
Carpenter, JR;
Rucker, G;
(2015)
Meta-analysis with R.
Springer International Publishing, New York.
ISBN 9783319214153
http://researchonline.lshtm.ac.uk/id/eprint/2319347
Full text not available from this repository.
Stirrup, OT;
Babiker, AG;
Carpenter, JR;
Copas, AJ;
(2015)
Fractional Brownian motion and multivariate-t models for longitudinal biomedical data, with application to CD4 counts in HIV-patients.
Statistics in medicine, 35 (9).
pp. 1514-32.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.6788
Full text not available from this repository.
Welch, CA;
Petersen, I;
Bartlett, JW;
White, IR;
Marston, L;
Morris, RW;
Nazareth, I;
Walters, K;
Carpenter, J;
(2014)
Evaluation of two-fold fully conditional specification multiple imputation for longitudinal electronic health record data.
Statistics in medicine, 33 (21).
pp. 3725-37.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.6184
Full text not available from this repository.
Williamson, E;
Morley, R;
Lucas, A;
Carpenter, J;
(2011)
Propensity scores: From naive enthusiasm to intuitive understanding.
Statistical methods in medical research, 21 (3).
pp. 273-293.
ISSN 0962-2802
DOI: https://doi.org/10.1177/0962280210394483
Full text not available from this repository.
Williamson, EJ;
Morley, R;
Lucas, A;
Carpenter, JR;
(2012)
Variance estimation for stratified propensity score estimators.
Statistics in medicine, 31 (15).
pp. 1617-32.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.4504
Full text not available from this repository.
Public
Barber, ND;
Alldred, DP;
Raynor, DK;
Dickinson, R;
Garfield, S;
Jesson, B;
Lim, R;
Savage, I;
Standage, C;
Buckle, P;
+4 more...
Carpenter, J;
Franklin, B;
Woloshynowych, M;
Zermansky, AG;
(2009)
Care homes' use of medicines study: prevalence, causes and potential harm of medication errors in care homes for older people.
Quality & safety in health care, 18 (5).
pp. 341-6.
ISSN 1475-3898
DOI: https://doi.org/10.1136/qshc.2009.034231
Bartlett, JW;
Carpenter, JR;
Tilling, K;
Vansteelandt, S;
(2014)
Improving upon the efficiency of complete case analysis when covariates are MNAR.
Biostatistics (Oxford, England), 15 (4).
pp. 719-30.
ISSN 1465-4644
DOI: https://doi.org/10.1093/biostatistics/kxu023
Bartlett, JW;
Carpenter, JR;
Tilling, K;
Vansteelandt, S;
(2015)
Corrigendum: Improving upon the efficiency of complete case analysis when covariates are MNAR (10.1093/biostatistics/kxu023).
Biostatistics (Oxford, England), 16 (1).
p. 205.
ISSN 1465-4644
DOI: https://doi.org/10.1093/biostatistics/kxu051
Bartlett, JW;
Harel, O;
Carpenter, JR;
(2015)
Asymptotically unbiased estimation of exposure odds ratios in complete records logistic regression.
American journal of epidemiology, 182 (8).
pp. 730-6.
ISSN 0002-9262
DOI: https://doi.org/10.1093/aje/kwv114
Bartlett, JW;
Seaman, SR;
White, IR;
Carpenter, JR;
Alzheimer's Disease Neuroimaging Initiative*;
(2014)
Multiple imputation of covariates by fully conditional specification: Accommodating the substantive model.
Statistical methods in medical research, 24 (4).
pp. 462-87.
ISSN 0962-2802
DOI: https://doi.org/10.1177/0962280214521348
Carpenter, JR;
Kenward, MG;
(2007)
Missing data in randomised controlled trials: a practical guide.
Health Technology Assessment Methodology Programme, Birmingham, p. 199.
http://researchonline.lshtm.ac.uk/id/eprint/4018500
Cornish, RP;
Macleod, J;
Carpenter, JR;
Tilling, K;
(2017)
Multiple imputation using linked proxy outcome data resulted in important bias reduction and efficiency gains: a simulation study.
Emerging themes in epidemiology, 14.
p. 14.
ISSN 1742-7622
DOI: https://doi.org/10.1186/s12982-017-0068-0
Ewings, FM;
Ford, D;
Walker, AS;
Carpenter, J;
Copas, A;
(2014)
Optimal CD4 Count for Initiating HIV Treatment: Impact of CD4 Observation Frequency and Grace Periods, and Performance of Dynamic Marginal Structural Models.
Epidemiology (Cambridge, Mass), 25 (2).
pp. 194-202.
ISSN 1044-3983
DOI: https://doi.org/10.1097/EDE.0000000000000043
Falcaro, M;
Carpenter, JR;
(2017)
Correcting bias due to missing stage data in the non-parametric estimation of stage-specific net survival for colorectal cancer using multiple imputation.
Cancer epidemiology, 48.
pp. 16-21.
ISSN 1877-7821
DOI: https://doi.org/10.1016/j.canep.2017.02.005
Fisher, DJ;
Carpenter, JR;
Morris, TP;
Freeman, SC;
Tierney, JF;
(2017)
Meta-analytical methods to identify who benefits most from treatments: daft, deluded, or deft approach?
BMJ (Clinical research ed), 356.
j573.
ISSN 0959-8138
DOI: https://doi.org/10.1136/bmj.j573
Freeman, SC;
Carpenter, JR;
(2017)
Bayesian one-step IPD network meta-analysis of time-to-event data using Royston-Parmar models.
Research synthesis methods.
ISSN 1759-2879
DOI: https://doi.org/10.1002/jrsm.1253
Freeman, SC;
Fisher, D;
Tierney, JF;
Carpenter, JR;
(2018)
A framework for identifying treatment-covariate interactions in individual participant data network meta-analysis.
Research synthesis methods.
ISSN 1759-2879
DOI: https://doi.org/10.1002/jrsm.1300
Gilham, C;
Rake, C;
Burdett, G;
Nicholson, AG;
Davison, L;
Franchini, A;
Carpenter, J;
Hodgson, J;
Darnton, A;
Peto, J;
(2015)
Pleural mesothelioma and lung cancer risks in relation to occupational history and asbestos lung burden.
Occupational and environmental medicine, 73 (5).
pp. 290-9.
ISSN 1351-0711
DOI: https://doi.org/10.1136/oemed-2015-103074
Hughes, RA;
White, IR;
Seaman, SR;
Carpenter, JR;
Tilling, K;
Sterne, JA;
(2014)
Joint modelling rationale for chained equations.
BMC medical research methodology, 14.
p. 28.
ISSN 1471-2288
DOI: https://doi.org/10.1186/1471-2288-14-28
Jackson, D;
White, IR;
Seaman, S;
Evans, H;
Baisley, K;
Carpenter, J;
(2014)
Relaxing the independent censoring assumption in the Cox proportional hazards model using multiple imputation.
Statistics in medicine, 33 (27).
pp. 4681-94.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.6274
Leurent, B;
Gomes, M;
Carpenter, JR;
(2018)
Missing data in trial-based cost-effectiveness analysis: An incomplete journey.
Health economics.
ISSN 1057-9230
DOI: https://doi.org/10.1002/hec.3654
Leurent, B;
Gomes, M;
Faria, R;
Morris, S;
Grieve, R;
Carpenter, JR;
(2018)
Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis: A Tutorial.
PharmacoEconomics.
ISSN 1170-7690
DOI: https://doi.org/10.1007/s40273-018-0650-5
Leyrat, C;
Seaman, SR;
White, IR;
Douglas, I;
Smeeth, L;
Kim, J;
Resche-Rigon, M;
Carpenter, JR;
Williamson, EJ;
(2017)
Propensity score analysis with partially observed covariates: How should multiple imputation be used?
Statistical methods in medical research.
p. 962280217713032.
ISSN 0962-2802
DOI: https://doi.org/10.1177/0962280217713032
Marston, L;
Carpenter, JR;
Walters, KR;
Morris, RW;
Nazareth, I;
White, IR;
Petersen, I;
(2014)
Smoker, ex-smoker or non-smoker? The validity of routinely recorded smoking status in UK primary care: a cross-sectional study.
BMJ open, 4 (4).
e004958.
ISSN 2044-6055
DOI: https://doi.org/10.1136/bmjopen-2014-004958
Mason, AJ;
Gomes, M;
Grieve, R;
Carpenter, JR;
(2018)
A Bayesian framework for health economic evaluation in studies with missing data.
Health economics.
ISSN 1057-9230
DOI: https://doi.org/10.1002/hec.3793
Mason, AJ;
Gomes, M;
Grieve, R;
Ulug, P;
Powell, JT;
Carpenter, J;
(2017)
Development of a practical approach to expert elicitation for randomised controlled trials with missing health outcomes: Application to the IMPROVE trial.
Clinical trials (London, England).
p. 1740774517711442.
ISSN 1740-7745
DOI: https://doi.org/10.1177/1740774517711442
Morris, TP;
Fisher, DJ;
Kenward, MG;
Carpenter, JR;
(2018)
Meta-analysis of Gaussian individual patient data: two-stage or not two-stage?
Statistics in medicine.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.7589
Nieminen, P;
Carpenter, J;
Rucker, G;
Schumacher, M;
(2006)
The relationship between quality of research and citation frequency.
BMC Med Res Methodol, 6.
p. 42.
ISSN 1471-2288
http://europepmc.org/articles/PMC1570136
Pham, TM;
Carpenter, JR;
Morris, TP;
Wood, AM;
Petersen, I;
(2018)
Population-calibrated multiple imputation for a binary/categorical covariate in categorical regression models.
Statistics in medicine.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.8004
Quartagno, M;
Carpenter, J;
(2018)
Multilevel Multiple Imputation in presence of interactions, non-linearities and random slopes
Imputazione Multipla Multilivello in presenza di interazioni, non-linearit`a e pendenze casuali.
[Conference or Workshop Item]
http://researchonline.lshtm.ac.uk/id/eprint/4648780
Quartagno, M;
Carpenter, JR;
(2015)
Multiple imputation for IPD meta-analysis: allowing for heterogeneity and studies with missing covariates.
Statistics in medicine, 35 (17).
pp. 2938-54.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.6837
Quartagno, M;
Walker, AS;
Carpenter, JR;
Phillips, PP;
Parmar, MK;
(2018)
Rethinking non-inferiority: a practical trial design for optimising treatment duration.
Clinical trials (London, England).
p. 1740774518778027.
ISSN 1740-7745
DOI: https://doi.org/10.1177/1740774518778027
Rehal, S;
Morris, TP;
Fielding, K;
Carpenter, JR;
Phillips, PP;
(2016)
Non-inferiority trials: are they inferior? A systematic review of reporting in major medical journals.
BMJ open, 6 (10).
e012594.
ISSN 2044-6055
DOI: https://doi.org/10.1136/bmjopen-2016-012594
Reiss, K;
Andersen, K;
Barnard, S;
Ngo, TD;
Biswas, K;
Smith, C;
Carpenter, J;
Church, K;
Nuremowla, S;
Pearson, E;
(2017)
Using automated voice messages linked to telephone counselling to increase post-menstrual regulation contraceptive uptake and continuation in Bangladesh: study protocol for a randomised controlled trial.
BMC public health, 17 (1).
p. 769.
ISSN 1471-2458
DOI: https://doi.org/10.1186/s12889-017-4703-z
Sauerbrei, W;
Abrahamowicz, M;
Altman, DG;
le Cessie, S;
Carpenter, J;
STRATOS initiative;
, COLLABORATORS;
Abrahamowicz, M;
Andersen, PK;
Altman, D;
+42 more...
Becher, H;
Binder, H;
Blettner, M;
Bodicoat, D;
Bossuyt, P;
Carpenter, J;
Carroll, R;
Chadha-Boreham, H;
Collins, G;
De Stavola, B;
Duchateau, L;
Evans, S;
Freedman, L;
Gail, M;
Goetghebeur, E;
Gustafson, P;
Harrell, F;
Huebner, M;
Jenkner, C;
Kipnis, V;
Kuechenhoff, H;
le Cessie, S;
Lee, K;
Macaskill, P;
Moodie, E;
Pearce, N;
Quantin, C;
Rahnenfuehrer, J;
Royston, P;
Sauerbrei, W;
Schumacher, M;
Sekula, P;
Stefanski, L;
Steyerberg, E;
Therneau, T;
Tilling, K;
Vach, W;
Vickers, A;
Wacholder, S;
Waernbaum, I;
White, I;
Woodward, M;
(2014)
STRengthening Analytical Thinking for Observational Studies: the STRATOS initiative.
Statistics in medicine, 33 (30).
pp. 5413-32.
ISSN 0277-6715
DOI: https://doi.org/10.1002/sim.6265
Schroter, S;
Black, N;
Evans, S;
Carpenter, J;
Godlee, F;
Smith, R;
(2004)
Effects of training on quality of peer review: randomised controlled trial.
BMJ (Clinical research ed), 328 (7441).
pp. 673-677.
ISSN 0959-8138
DOI: https://doi.org/10.1136/bmj.38023.700775.AE
Shah, AD;
Bartlett, JW;
Carpenter, J;
Nicholas, O;
Hemingway, H;
(2014)
Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study.
American journal of epidemiology, 179 (6).
pp. 764-74.
ISSN 0002-9262
DOI: https://doi.org/10.1093/aje/kwt312
Smuk, M;
Carpenter, JR;
Morris, TP;
(2017)
What impact do assumptions about missing data have on conclusions? A practical sensitivity analysis for a cancer survival registry.
BMC medical research methodology, 17 (1).
p. 21.
ISSN 1471-2288
DOI: https://doi.org/10.1186/s12874-017-0301-0
Sterne, JA;
Hernán, MA;
Reeves, BC;
Savović, J;
Berkman, ND;
Viswanathan, M;
Henry, D;
Altman, DG;
Ansari, MT;
Boutron, I;
+25 more...
Carpenter, JR;
Chan, AW;
Churchill, R;
Deeks, JJ;
Hróbjartsson, A;
Kirkham, J;
Jüni, P;
Loke, YK;
Pigott, TD;
Ramsay, CR;
Regidor, D;
Rothstein, HR;
Sandhu, L;
Santaguida, PL;
Schünemann, HJ;
Shea, B;
Shrier, I;
Tugwell, P;
Turner, L;
Valentine, JC;
Waddington, H;
Waters, E;
Wells, GA;
Whiting, PF;
Higgins, JP;
(2016)
ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions.
BMJ (Clinical research ed), 355.
i4919.
ISSN 0959-8138
DOI: https://doi.org/10.1136/bmj.i4919
Tilling, K;
Williamson, EJ;
Spratt, M;
Sterne, JA;
Carpenter, JR;
(2016)
Appropriate inclusion of interactions was needed to avoid bias in multiple imputation.
Journal of clinical epidemiology, 80.
pp. 107-115.
ISSN 0895-4356
DOI: https://doi.org/10.1016/j.jclinepi.2016.07.004
Wing, K;
Williamson, E;
Carpenter, JR;
Wise, L;
Schneeweiss, S;
Smeeth, L;
Quint, JK;
Douglas, I;
(2018)
Real-world effects of medications for chronic obstructive pulmonary disease: protocol for a UK population-based non-interventional cohort study with validation against randomised trial results.
BMJ open, 8 (3).
e019475.
ISSN 2044-6055
DOI: https://doi.org/10.1136/bmjopen-2017-019475
Restricted
Goldstein, H;
Carpenter, J;
Kenward, M;
(2018)
Bayesian models for weighted data with missing values: a bootstrap approach.
Applied statistics.
ISSN 0035-9254
DOI: https://doi.org/10.1111/rssc.12259
Item availability may be restricted.
Hollestein, LM;
Carpenter, JR;
(2018)
Missing data in clinical research: an integrated approach.
The British journal of dermatology, 177 (6).
pp. 1463-1465.
ISSN 0007-0963
DOI: https://doi.org/10.1111/bjd.16010
Item availability may be restricted.
Leurent, B;
Gomes, M;
Carpenter, J;
(2018)
Comment on: Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis: A Tutorial.
PharmacoEconomics.
ISSN 1170-7690
DOI: https://doi.org/10.1007/s40273-018-0700-z
Item availability may be restricted.
Vergnaud, A.-, C;
Aresu, M;
Kongsgård, HW;
McRobie, D;
Singh, D;
Spear, J;
Heard, A;
Gao, H;
Carpenter, JR;
Elliott, P;
(2018)
Estimation of TETRA radio use in the Airwave Health Monitoring Study of the British police forces.
Environmental research.
ISSN 0013-9351
DOI: https://doi.org/10.1016/j.envres.2018.07.015
Item availability may be restricted.
White, IR;
Carpenter, J;
Horton, NJ;
(2017)
A mean score method for sensitivity analysis to departures from the missing at random assumption in randomised trials.
Statistica Sinica, 28 (4).
pp. 1985-2003.
ISSN 1017-0405
DOI: https://doi.org/10.5705/ss.202016.0308
Item availability may be restricted.