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Rhian M Daniel
Rhian M Daniel
Professor of Statistics, Division of Population Medicine, Cardiff University
Email verificata su cardiff.ac.uk - Home page
Titolo
Citata da
Citata da
Anno
Methods for dealing with time-dependent confounding
RM Daniel, SN Cousens, BL De Stavola, MG Kenward, JAC Sterne
Statistics in Medicine, 2012
4282012
Causal mediation analysis with multiple mediators
RM Daniel, BL De Stavola, SN Cousens, S Vansteelandt
Biometrics 71 (1), 1-14, 2015
3252015
Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways
S Burgess, RM Daniel, AS Butterworth, SG Thompson, ...
International journal of epidemiology 44 (2), 484-495, 2015
3082015
Outcome modelling strategies in epidemiology: traditional methods and basic alternatives
S Greenland, R Daniel, N Pearce
International journal of epidemiology 45 (2), 565-575, 2016
2582016
Interventional effects for mediation analysis with multiple mediators
S Vansteelandt, RM Daniel
Epidemiology 28 (2), 258-265, 2017
2432017
Avoiding bias due to perfect prediction in multiple imputation of incomplete categorical variables
IR White, R Daniel, P Royston
Computational statistics & data analysis 54 (10), 2267-2275, 2010
2372010
Incidence of community-acquired lower respiratory tract infections and pneumonia among older adults in the United Kingdom: a population-based study
ERC Millett, JK Quint, L Smeeth, RM Daniel, SL Thomas
PloS one 8 (9), e75131, 2013
2242013
gformula: Estimating causal effects in the presence of time-varying confounding or mediation using the g-computation formula
RM Daniel, BL De Stavola, SN Cousens
The Stata Journal 11 (4), 479-517, 2011
1942011
Using causal diagrams to guide analysis in missing data problems
RM Daniel, MG Kenward, SN Cousens, BL De Stavola
Statistical methods in medical research 21 (3), 243-256, 2012
1892012
On regression adjustment for the propensity score
S Vansteelandt, RM Daniel
Statistics in medicine 33 (23), 4053-4072, 2014
1862014
Mediation analysis with intermediate confounding: structural equation modeling viewed through the causal inference lens
BL De Stavola, RM Daniel, GB Ploubidis, N Micali
American journal of epidemiology 181 (1), 64-80, 2015
1632015
Making apples from oranges: Comparing noncollapsible effect estimators and their standard errors after adjustment for different covariate sets
R Daniel, J Zhang, D Farewell
Biometrical Journal 63 (3), 528-557, 2021
1112021
A comparison of methods to adjust for continuous covariates in the analysis of randomised trials
BC Kahan, H Rushton, TP Morris, RM Daniel
BMC medical research methodology 16, 1-10, 2016
722016
Commentary: The formal approach to quantitative causal inference in epidemiology: misguided or misrepresented?
RM Daniel, BL De Stavola, S Vansteelandt
International journal of epidemiology 45 (6), 1817-1829, 2016
722016
Analysis of longitudinal studies with repeated outcome measures: adjusting for time-dependent confounding using conventional methods
RH Keogh, RM Daniel, TJ VanderWeele, S Vansteelandt
American journal of epidemiology 187 (5), 1085-1092, 2018
482018
How much do tumor stage and treatment explain socioeconomic inequalities in breast cancer survival? Applying causal mediation analysis to population-based data
R Li, R Daniel, B Rachet
European journal of epidemiology 31, 603-611, 2016
482016
Time‐dependent mediators in survival analysis: modeling direct and indirect effects with the additive hazards model
OO Aalen, MJ Stensrud, V Didelez, R Daniel, K Røysland, S Strohmaier
Biometrical Journal 62 (3), 532-549, 2020
452020
The causal web of foetal alcohol spectrum disorders: a review and causal diagram
C McQuire, R Daniel, L Hurt, A Kemp, S Paranjothy
European child & adolescent psychiatry 29 (5), 575-594, 2020
442020
Analysis of tuberculosis prevalence surveys: new guidance on best-practice methods
S Floyd, C Sismanidis, N Yamada, R Daniel, J Lagahid, F Mecatti, ...
Emerging themes in epidemiology 10, 1-13, 2013
442013
The impact of a cash transfer programme on tuberculosis treatment success rate: a quasi-experimental study in Brazil
DJ Carter, R Daniel, AW Torrens, MN Sanchez, ELN Maciel, ...
BMJ global health 4 (1), e001029, 2019
382019
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