Moreno-Betancur M - Search Results

1

Multiple imputation methods for handling incomplete longitudinal and clustered data where the target analysis is a linear mixed effects model.

Huque MH, Moreno-Betancur M, Quartagno M, Simpson JA, Carlin JB, Lee KJ. Huque MH, et al. Biom J. 2020 Mar;62(2):444-466. doi: 10.1002/bimj.201900051. Epub 2020 Jan 9. Biom J. 2020. PMID: 31919921 Free PMC article.

2

Sensitivity analysis of incomplete longitudinal data departing from the missing at random assumption: Methodology and application in a clinical trial with drop-outs.

Moreno-Betancur M, Chavance M. Moreno-Betancur M, et al. Stat Methods Med Res. 2016 Aug;25(4):1471-89. doi: 10.1177/0962280213490014. Epub 2013 May 22. Stat Methods Med Res. 2016. PMID: 23698867

3

Vitamin D insufficiency in the first 6 months of infancy and challenge-proven IgE-mediated food allergy at 1 year of age: a case-cohort study.

Molloy J, Koplin JJ, Allen KJ, Tang MLK, Collier F, Carlin JB, Saffery R, Burgner D, Ranganathan S, Dwyer T, Ward AC, Moreno-Betancur M, Clarke M, Ponsonby AL, Vuillermin P; BIS Investigator Group. Molloy J, et al. Allergy. 2017 Aug;72(8):1222-1231. doi: 10.1111/all.13122. Epub 2017 Feb 23. Allergy. 2017. PMID: 28042676

4

A comparison of multiple imputation methods for handling missing values in longitudinal data in the presence of a time-varying covariate with a non-linear association with time: a simulation study.

De Silva AP, Moreno-Betancur M, De Livera AM, Lee KJ, Simpson JA. De Silva AP, et al. BMC Med Res Methodol. 2017 Jul 25;17(1):114. doi: 10.1186/s12874-017-0372-y. BMC Med Res Methodol. 2017. PMID: 28743256 Free PMC article.

5

Measuring the impact of differences in risk factor distributions on cross-population differences in disease occurrence: a causal approach.

Moreno-Betancur M, Koplin JJ, Ponsonby AL, Lynch J, Carlin JB. Moreno-Betancur M, et al. Int J Epidemiol. 2018 Feb 1;47(1):217-225. doi: 10.1093/ije/dyx194. Int J Epidemiol. 2018. PMID: 29025097

6

Survival analysis with time-dependent covariates subject to missing data or measurement error: Multiple Imputation for Joint Modeling (MIJM).

Moreno-Betancur M, Carlin JB, Brilleman SL, Tanamas SK, Peeters A, Wolfe R. Moreno-Betancur M, et al. Biostatistics. 2018 Oct 1;19(4):479-496. doi: 10.1093/biostatistics/kxx046. Biostatistics. 2018. PMID: 29040396 Free PMC article.

7

On the use of the not-at-random fully conditional specification (NARFCS) procedure in practice.

Tompsett DM, Leacy F, Moreno-Betancur M, Heron J, White IR. Tompsett DM, et al. Stat Med. 2018 Jul 10;37(15):2338-2353. doi: 10.1002/sim.7643. Epub 2018 Apr 2. Stat Med. 2018. PMID: 29611205 Free PMC article.

8

Understanding Interventional Effects: A More Natural Approach to Mediation Analysis?

Moreno-Betancur M, Carlin JB. Moreno-Betancur M, et al. Epidemiology. 2018 Sep;29(5):614-617. doi: 10.1097/EDE.0000000000000866. Epidemiology. 2018. PMID: 29864082

9

Canonical Causal Diagrams to Guide the Treatment of Missing Data in Epidemiologic Studies.

Moreno-Betancur M, Lee KJ, Leacy FP, White IR, Simpson JA, Carlin JB. Moreno-Betancur M, et al. Am J Epidemiol. 2018 Dec 1;187(12):2705-2715. doi: 10.1093/aje/kwy173. Am J Epidemiol. 2018. PMID: 30124749 Free PMC article.

10

Joint longitudinal and time-to-event models for multilevel hierarchical data.

Brilleman SL, Crowther MJ, Moreno-Betancur M, Buros Novik J, Dunyak J, Al-Huniti N, Fox R, Hammerbacher J, Wolfe R. Brilleman SL, et al. Stat Methods Med Res. 2019 Dec;28(12):3502-3515. doi: 10.1177/0962280218808821. Epub 2018 Oct 31. Stat Methods Med Res. 2019. PMID: 30378472

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