Rhian M Daniel
Rhian M Daniel
Professor of Statistics, Division of Population Medicine, Cardiff University
Verified email at - Homepage
Cited by
Cited by
Methods for dealing with time-dependent confounding
RM Daniel, SN Cousens, BL De Stavola, MG Kenward, JAC Sterne
Statistics in Medicine, 2012
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
Causal mediation analysis with multiple mediators
RM Daniel, BL De Stavola, SN Cousens, S Vansteelandt
Biometrics 71 (1), 1-14, 2015
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
Interventional effects for mediation analysis with multiple mediators
S Vansteelandt, RM Daniel
Epidemiology 28 (2), 258-265, 2017
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
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
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
On regression adjustment for the propensity score
S Vansteelandt, RM Daniel
Statistics in medicine 33 (23), 4053-4072, 2014
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
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
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
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
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
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
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
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
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
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 R°ysland, S Strohmaier
Biometrical Journal 62 (3), 532-549, 2020
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
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