Sensitivity analyses for data missing at random versus missing not at random using latent growth modelling: a practical guide for randomised controlled trials

Sensitivity analyses for data missing at random versus missing not at random using latent growth modelling: a practical guide for randomised controlled trials

Abstract Background Missing data are ubiquitous in randomised controlled trials. Although sensitivity analyses for different missing data mechanisms (missing at random vs. missing not at random) are widely recommended, they are rarely conducted in practice. The aim of the present study was to demons...

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Bibliographic Details
Main Authors: Andreas Staudt, Jennis Freyer-Adam, Till Ittermann, Christian Meyer, Gallus Bischof, Ulrich John, Sophie Baumann
Format: Article
Language:English
Published: BMC 2022-09-01
Series:BMC Medical Research Methodology
Subjects:
MAR
MNAR
Growth curve model
Participant attrition
Dropout
Online Access:https://doi.org/10.1186/s12874-022-01727-1

Internet

https://doi.org/10.1186/s12874-022-01727-1

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