Rhian M Daniel
Rhian M Daniel
Reader, Division of Population Medicine, Cardiff University
Email verificata su cardiff.ac.uk - Home page
Citata da
Citata da
Methods for dealing with time-dependent confounding
RM Daniel, SN Cousens, BL De Stavola, MG Kenward, JAC Sterne
Statistics in Medicine, 2012
Causal mediation analysis with multiple mediators
RM Daniel, BL De Stavola, SN Cousens, S Vansteelandt
Biometrics 71 (1), 1-14, 2015
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
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
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
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
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
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
Interventional effects for mediation analysis with multiple mediators
S Vansteelandt, RM Daniel
Epidemiology (Cambridge, Mass.) 28 (2), 258, 2017
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
On regression adjustment for the propensity score
S Vansteelandt, RM Daniel
Statistics in medicine 33 (23), 4053-4072, 2014
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
Consortium EP-I. Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways
S Burgess, RM Daniel, AS Butterworth, SG Thompson
Int J Epidemiol 44 (2), 484-95, 2015
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), 1-10, 2016
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), 1-13, 2013
A method for increasing the robustness of multiple imputation
RM Daniel, MG Kenward
Computational Statistics & Data Analysis 56 (6), 1624-1643, 2012
Response and non-response to a quality-of-life question on sexual life: a case study of the simple mean imputation method
YB Cheung, R Daniel, GY Ng
Quality of Life Research 15 (9), 1493-1501, 2006
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 (6), 603-611, 2016
Commentary: Marginal Structural Models The Way Forward for Life-course Epidemiology?
BL De Stavola, RM Daniel
Epidemiology 23 (2), 233-237, 2012
Poor outcomes in hospitalized patients with gastrointestinal bleeding: impact of baseline risk, bleeding severity, and process of care
V Jairath, J Thompson, BC Kahan, R Daniel, SA Hearnshaw, SPL Travis, ...
American Journal of Gastroenterology 109 (10), 1603-1612, 2014
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