Deng, NinaAllison, Jeroan J.Fang, Hua (Julia)Ash, Arlene S.Ware, John E. Jr.2022-08-232022-08-232013-05-312013-09-18Health Qual Life Outcomes. 2013 May 31;11:89. doi: 10.1186/1477-7525-11-89. <a href="http://dx.doi.org/10.1186/1477-7525-11-89" target="_blank">Link to article on publisher's website</a>1477-752510.1186/1477-7525-11-8923721463https://hdl.handle.net/20.500.14038/46652BACKGROUND: Relative validity (RV), a ratio of ANOVA F-statistics, is often used to compare the validity of patient-reported outcome (PRO) measures. We used the bootstrap to establish the statistical significance of the RV and to identify key factors affecting its significance. METHODS: Based on responses from 453 chronic kidney disease (CKD) patients to 16 CKD-specific and generic PRO measures, RVs were computed to determine how well each measure discriminated across clinically-defined groups of patients compared to the most discriminating (reference) measure. Statistical significance of RV was quantified by the 95% bootstrap confidence interval. Simulations examined the effects of sample size, denominator F-statistic, correlation between comparator and reference measures, and number of bootstrap replicates. RESULTS: The statistical significance of the RV increased as the magnitude of denominator F-statistic increased or as the correlation between comparator and reference measures increased. A denominator F-statistic of 57 conveyed sufficient power (80%) to detect an RV of 0.6 for two measures correlated at r = 0.7. Larger denominator F-statistics or higher correlations provided greater power. Larger sample size with a fixed denominator F-statistic or more bootstrap replicates (beyond 500) had minimal impact. CONCLUSIONS: The bootstrap is valuable for establishing the statistical significance of RV estimates. A reasonably large denominator F-statistic (F > 57) is required for adequate power when using the RV to compare the validity of measures with small or moderate correlations (r < 0.7). Substantially greater power can be achieved when comparing measures of a very high correlation (r > 0.9).en-US<p>© 2013 Deng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>AdultAnalysis of VarianceConfidence IntervalsFemaleHealth StatusHumansMaleModels, StatisticalOutcome Assessment (Health Care)Quality of LifeRenal Insufficiency, ChronicSelf ReportBiostatisticsEpidemiologyHealth Services ResearchJournal Articlehttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=2113&amp;context=qhs_pp&amp;unstamped=1https://escholarship.umassmed.edu/qhs_pp/11114598961qhs_pp/1111