Using the bootstrap to establish statistical significance for relative validity comparisons among patient-reported outcome measures.
Using the bootstrap to establish statistical significance for relative validity comparisons among patient-reported outcome measures.
复制标题
DOI：
10.1186/1477-7525-11-89
复制
发表时间：
2013-05-31
影响因子：
3.6
通讯作者：
Ware JE Jr
中科院分区：
文献类型：
--
作者：
Deng N;Allison JJ;Fang HJ;Ash AS;Ware JE Jr
相对有效性（RV）是方差分析F统计量的比率，通常用于比较患者报告结局（PRO）指标的有效性。我们使用自举法建立RV的统计学显著性，并确定影响其显著性的关键因素。基于453例慢性肾脏病（CKD）患者对16项CKD特异性和通用PRO指标的反应，计算RV，以确定与最具鉴别力（参考）指标相比，每项指标在临床定义的患者组中的鉴别程度。RV的统计学显著性通过95% bootstrap置信区间量化。模拟检查了样本量、分母F统计量、比较指标和参考指标之间的相关性以及自助重复次数的影响。RV的统计学显著性随着分母F统计量的大小增加或对照和参考测量值之间的相关性增加而增加。分母F-统计量为57，具有足够的把握度（80%），可检测到r = 0.7时相关的两个测量值的RV为0.6。较大的分母F统计量或较高的相关性提供了更大的功效。具有固定分母F统计量的较大样本量或更多自助重复（超过500）的影响极小。自助法对于确定RV估计值的统计学显著性很有价值。当使用RV比较具有小或中等相关性（r < 0.7）的测量值的有效性时，需要合理的大分母F统计量（F > 57）以获得足够的功效。当比较非常高相关性（r > 0.9）的测量时，可以实现显著更大的功效。
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. 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. 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. 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).
登录
查看更多内容
影响因子：
3
作者：
Kosinski, M;Keller, SD;Kong, SXD
通讯作者：
Kong, SXD
影响因子：
7.2
作者：
Hart, DL;Cook, KF;Crane, PK
通讯作者：
Crane, PK
影响因子：
158.5
作者：
EVANS, RW;MANNINEN, DL;LOWRIE, EG
通讯作者：
LOWRIE, EG
影响因子：
3
作者：
LIANG, MH;FOSSEL, AH;LARSON, MG
通讯作者：
LARSON, MG
影响因子：
3
作者：
Norquist, JM;Fitzpatrick, R;Jenkinson, C
通讯作者：
Jenkinson, C