Multiple imputation methods for bivariate outcomes in cluster randomised trials: Supporting Information

Diaz-ordaz, K, Kenward, M, Gomes, M and Grieve, R. 2016. Multiple imputation methods for bivariate outcomes in cluster randomised trials: Supporting Information. [Online]. London School of Hygiene & Tropical Medicine, London, United Kingdom. Available from: https://doi.org/10.17037/DATA.99.

Diaz-ordaz, K, Kenward, M, Gomes, M and Grieve, R. Multiple imputation methods for bivariate outcomes in cluster randomised trials: Supporting Information. [Internet] LSHTM Data Compass. London, United Kingdom: London School of Hygiene & Tropical Medicine; 2016. Available from: https://doi.org/10.17037/DATA.99.

Diaz-ordaz, K, Kenward, M, Gomes, M and Grieve, R (2016). Multiple imputation methods for bivariate outcomes in cluster randomised trials: Supporting Information. [Data Collection]. London School of Hygiene & Tropical Medicine, London, United Kingdom. https://doi.org/10.17037/DATA.99.

Description

Data capture method Simulation
Date (Published in a 3rd party system) 14 March 2016
Language(s) of written materials English
Funders
ProjectFunderGrant NumberFunder URI
UNSPECIFIEDMedical Research CouncilUNSPECIFIEDUNSPECIFIED
UNSPECIFIEDNHS National Institute for Health ResearchUNSPECIFIEDUNSPECIFIED
Depositor LSHTM Library & Archives Service
Date Deposited 23 Mar 2016 12:01
Last Modified 23 Mar 2016 12:01
Publisher London School of Hygiene & Tropical Medicine

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Study Instrument

Filename: Data_Generating_Function.R

Description: R code created to model influencing factors that affect the handling of missing data

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Content type: Software

File size: 13kB

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