Danielle L Burke

Publication Activity (10 Years)

Years Active: 2016-2020
Publications (10 Years): 8

Top Topics

African American

Systematic Review

Pregnancy Outcomes

Top Venues

Statistics in medicine

Research synthesis methods

Prenatal diagnosis

This page only lists publications with an associated author ORCID identifier.

Publications

Richard D Riley, Amardeep Legha, Dan Jackson, Tim P Morris, Joie Ensor, Kym I E Snell, Ian R White, Danielle L Burke
One-stage individual participant data meta-analysis models for continuous and binary outcomes: Comparison of treatment coding options and estimation methods. Statistics in medicine 39 (19) (2020)
Richard D Riley, Kym Ie Snell, Joie Ensor, Danielle L Burke, Frank E Harrell, Karel Gm Moons, Gary Stephen Collins
Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes. Statistics in medicine 38 (7) (2018)
Richard D Riley, Kym I E Snell, Joie Ensor, Danielle L Burke, Frank E Harrell, Karel G M Moons, Gary Stephen Collins
Minimum sample size for developing a multivariable prediction model: Part I - Continuous outcomes. Statistics in medicine 38 (7) (2018)
Amardeep Legha, Richard D Riley, Joie Ensor, Kym I E Snell, Tim P Morris, Danielle L Burke
Individual participant data meta-analysis of continuous outcomes: A comparison of approaches for specifying and estimating one-stage models. Statistics in medicine 37 (29) (2018)
Danielle L Burke, Joie Ensor, Kym I E Snell, Danielle van der Windt, Richard D Riley
Guidance for deriving and presenting percentage study weights in meta-analysis of test accuracy studies. Research synthesis methods 9 (2) (2018)
Ashwini Bilagi, Danielle L Burke, Richard D Riley, Ian Mills, Mark D Kilby, R Katie Morris
Association of maternal serum PAPP-A levels, nuchal translucency and crown-rump length in first trimester with adverse pregnancy outcomes: retrospective cohort study. Prenatal diagnosis 37 (7) (2017)
Danielle L Burke, Joie Ensor, Richard D Riley
Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ. Statistics in medicine 36 (5) (2016)
Hairui Hua, Danielle L Burke, Michael J Crowther, Joie Ensor, Catrin Tudur Smith, Richard D Riley
One-stage individual participant data meta-analysis models: estimation of treatment-covariate interactions must avoid ecological bias by separating out within-trial and across-trial information. Statistics in medicine 36 (5) (2016)