Evaluating the evaluation
Vance W Berger National Cancer Institute, University of Maryland Baltimore County, Biometry Research Group, Rockville, MD, USAZhang et al1 sought to determine which adjustment method is the best. That is a laudable objective, but their approach leaves quite a bit to be desired. When we cut to the ch...
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Veröffentlicht in: | Clinical epidemiology 2015-01, Vol.7 (default), p.117-118 |
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Sprache: | eng |
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Zusammenfassung: | Vance W Berger National Cancer Institute, University of Maryland Baltimore County, Biometry Research Group, Rockville, MD, USAZhang et al1 sought to determine which adjustment method is the best. That is a laudable objective, but their approach leaves quite a bit to be desired. When we cut to the chase, we find that they pre-supposed that the analysis of covariance (ANCOVA) was ideal, and, presumably, confirmed this empirically by noting that the ANCOVA results were most aligned with the ANCOVA gold standard. This is fairly perplexing logic. Had any of the other methods been chosen instead as the gold standard, then that method would have been found to be the best by virtue of agreeing with its own results. This is hardly a compelling endorsement. Beyond that, even if the authors did use a more reasoned approach, how can one trial be used to validate an analysis?View original paper by Zhang and colleagues. |
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ISSN: | 1179-1349 1179-1349 |
DOI: | 10.2147/CLEP.S79643 |