Kenward MG - Search Results

1

Multiple imputation methods for bivariate outcomes in cluster randomised trials.

DiazOrdaz K, Kenward MG, Gomes M, Grieve R. DiazOrdaz K, et al. Among authors: kenward mg. Stat Med. 2016 Sep 10;35(20):3482-96. doi: 10.1002/sim.6935. Epub 2016 Mar 14. Stat Med. 2016. PMID: 26990655 Free PMC article.

2

Are missing data adequately handled in cluster randomised trials? A systematic review and guidelines.

Díaz-Ordaz K, Kenward MG, Cohen A, Coleman CL, Eldridge S. Díaz-Ordaz K, et al. Among authors: kenward mg. Clin Trials. 2014 Oct;11(5):590-600. doi: 10.1177/1740774514537136. Epub 2014 Jun 5. Clin Trials. 2014. PMID: 24902924 Review.

3

Estimating treatment effects under untestable assumptions with nonignorable missing data.

Gomes M, Kenward MG, Grieve R, Carpenter J. Gomes M, et al. Among authors: kenward mg. Stat Med. 2020 May 20;39(11):1658-1674. doi: 10.1002/sim.8504. Epub 2020 Feb 14. Stat Med. 2020. PMID: 32059073

4

Multiple imputation methods for handling missing data in cost-effectiveness analyses that use data from hierarchical studies: an application to cluster randomized trials.

Gomes M, Díaz-Ordaz K, Grieve R, Kenward MG. Gomes M, et al. Among authors: kenward mg. Med Decis Making. 2013 Nov;33(8):1051-63. doi: 10.1177/0272989X13492203. Epub 2013 Aug 1. Med Decis Making. 2013. PMID: 23913915 Free article.

5

Analysis of longitudinal trials with protocol deviation: a framework for relevant, accessible assumptions, and inference via multiple imputation.

Carpenter JR, Roger JH, Kenward MG. Carpenter JR, et al. Among authors: kenward mg. J Biopharm Stat. 2013;23(6):1352-71. doi: 10.1080/10543406.2013.834911. J Biopharm Stat. 2013. PMID: 24138436

6

Sensitivity analysis for clinical trials with missing continuous outcome data using controlled multiple imputation: A practical guide.

Cro S, Morris TP, Kenward MG, Carpenter JR. Cro S, et al. Among authors: kenward mg. Stat Med. 2020 Sep 20;39(21):2815-2842. doi: 10.1002/sim.8569. Epub 2020 May 17. Stat Med. 2020. PMID: 32419182

7

Optimizing the design of clinical trials where the outcome is a rate. Can estimating a baseline rate in a run-in period increase efficiency?

Frost C, Kenward MG, Fox NC. Frost C, et al. Among authors: kenward mg. Stat Med. 2008 Aug 30;27(19):3717-31. doi: 10.1002/sim.3280. Stat Med. 2008. PMID: 18484598

8

Response to comments by Seaman et al. on "Analysis of longitudinal trials with protocol deviation: a framework for relevant, accessible assumptions, and inference via multiple imputation," Journal of Biopharmaceutical Statistics 23:1352-1371.

Carpenter JR, Roger JH, Cro S, Kenward MG. Carpenter JR, et al. Among authors: kenward mg. J Biopharm Stat. 2014;24(6):1363-9. doi: 10.1080/10543406.2014.960085. J Biopharm Stat. 2014. PMID: 25215553 No abstract available.

9

Methods for dealing with time-dependent confounding.

Daniel RM, Cousens SN, De Stavola BL, Kenward MG, Sterne JA. Daniel RM, et al. Among authors: kenward mg. Stat Med. 2013 Apr 30;32(9):1584-618. doi: 10.1002/sim.5686. Epub 2012 Dec 3. Stat Med. 2013. PMID: 23208861

10

Meta-analysis of Gaussian individual patient data: Two-stage or not two-stage?

Morris TP, Fisher DJ, Kenward MG, Carpenter JR. Morris TP, et al. Among authors: kenward mg. Stat Med. 2018 Apr 30;37(9):1419-1438. doi: 10.1002/sim.7589. Epub 2018 Jan 18. Stat Med. 2018. PMID: 29349792 Free PMC article.

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