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|Title: ||Recent Developments in the Prevention and Treatment of Missing Data|
|Authors: ||Mallinckrodt, Craig|
|Issue Date: ||2014|
|Citation: ||THERAPEUTIC INNOVATION & REGULATORY SCIENCE, 48 (1), p. 68-80|
|Abstract: ||Recent research has fostered new guidance on preventing and treating missing data, most notably the landmark expert panel report from the National Research Council (NRC) that was commissioned by FDA. One of the findings from that panel was the need for better software tools to conduct missing data sensitivity analyses and frameworks for drawing inference from them. In response to the NRC recommendations, a Scientific Working Group was formed under the Auspices of the Drug Information Association (DIASWG). The present paper is from work of the DIASWG. Specifically, the NRC panel's 18 recommendations are distilled into 3 pillars for dealing with missing data: (1) providing clearly stated objectives and causal estimands; (2) preventing as much missing data as possible; and (3) combining a sensible primary analysis with sensitivity analyses to assess robustness of inferences to missing data assumptions. Sample data sets are used to illustrate how sensitivity analyses can be used to assess robustness of inferences to missing data assumptions. The suite of software tools used to conduct the sensitivity analyses are freely available for public use at www.missingdata.org.uk.|
|Notes: ||Mallinckrodt, C (reprint author), Mallinckrodt, C (reprint author) Eli Lilly & Co, Lilly Res Labs, Indianapolis, IN 46285 USA.
|ISI #: ||000329164100009|
|Type: ||Journal Contribution|
|Validation: ||ecoom, 2015|
|Appears in Collections: ||Research publications|
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|Published version||350.26 kB||Adobe PDF|
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