The Prevention and Treatment of Missing Data in Clinical Trials¶
National Research Council. (2010). The Prevention and Treatment of Missing Data in Clinical Trials. National Academies Press.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Mechanisms¶
- Missingness Indicator Matrix
- Profile the structure. Cross-tabulate absence by variable, unit, wave, site, or device, and flag whether patterns are monotone (once gone, stays gone) or intermittent.
This sourceDistinguishes monotone dropout patterns, where later observations stay missing, from intermittent nonmonotone missingness.
- Profile the structure. Cross-tabulate absence by variable, unit, wave, site, or device, and flag whether patterns are monotone (once gone, stays gone) or intermittent.
- Tipping-Point Analysis
- Its strength is honesty under irreducible ignorance: when the mechanism cannot be pinned down, it converts the anxiety about dropouts into a concrete, communicable boundary and lets stakeholders — regulators especially — decide whether that boundary is reachable.
This sourceRecommends transparent sensitivity analyses that vary unverifiable missing-data assumptions and show how conclusions change across plausible values.
- Its strength is honesty under irreducible ignorance: when the mechanism cannot be pinned down, it converts the anxiety about dropouts into a concrete, communicable boundary and lets stakeholders — regulators especially — decide whether that boundary is reachable.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Not recorded. Neither this nor any other of the 2 citations of this work carries a recorded support check.
Was it audited? Yes. A second, independent pass read the citation against the article text and recorded a verdict.
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Registry ID ref:91a36e86602b · see in the full table