Re-analysis of data from a cluster RCT entitled "health literacy and exercise-focused interventions on clinical measurements in Chinese diabetes patients".
Re-analysis of data from a cluster RCT entitled "health literacy and exercise-focused interventions on clinical measurements in Chinese diabetes patients".
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DOI：
10.1016/j.eclinm.2022.101686
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发表时间：
2022-11
影响因子：
15.1
通讯作者：
Allison, David B.
中科院分区：
文献类型：
--
作者：
Jamshidi-Naeini, Yasaman;Golzarri-Arroyo, Lilian;Vorland, Colby J.;Brown, Andrew W.;Allison, David B.
王等人。 1 在一项四组整群随机试验 (cRCT) 中检查了三种健康素养和运动干预措施对 HbA1c（主要结果）的影响，但没有考虑聚类和嵌套。八个医疗中心 (CHC) 被随机分配到四种情况（每种情况两个）。在登记后的四个时间点进行重复测量。对于 HbA1c 的干预效果，报告了名义上显着的 p 值。我们重新分析了聚类和嵌套的数据，并在本文中给出了结果。典型推论统计方法有效性的假设是观察的独立性：每个受访者的结果与其他受访者的结果无关。在 cRCT 中，聚类是随机的，但有关干预效果的推论通常是针对个体的。在这项研究中，来自同一 CHC（集群）的个体预计比来自不同集群的个体更相似，从而产生相关数据的模式，因此“错误”（模型残差）在个体参与者之间并不独立。 2, 3 来自同一簇的观测值之间的内在相关性通常会增加 I 类错误率。不考虑集群内的非独立性可能会导致方差估计不正确； p 值小于有效分析对干预效果产生的值；从而得出关于干预效果的无效推论。 4 有效分析是指在原假设下，使用连续分布的数据和连续分布的检验统计量，产生在区间 [0, 1] 上均匀的 p 值抽样分布的分析。无效分析是指产生任何其他 p 值抽样分布的测试程序。
Wang et al. 1 examined the effects of three health literacy and exercise interventions on HbA1c (the primary outcome) in a four-arm cluster randomized trial (cRCT), but did not account for clustering and nesting. Eight Healthcare Centers (CHCs) were randomly assigned to four conditions (two per condition). Repeated measurements occurred at four timepoints after enrollment. Nominally significant p-values were reported for intervention effects on HbA1c. We reanalyzed the data accounting for clustering and nesting, and present the results herein.An assumption underlying the validity of typical inferential statistical methods is independence of observations: the outcome of each respondent is not related to the outcomes of other respondents. In cRCTs, clusters are randomized, but inferences about the intervention effects are often intended to individuals. In the study, individuals from the same CHC (cluster) are expected to be more similar than those from different clusters, resulting in a pattern of correlated data so ‘errors’(model residuals) are not independent across individual participants. 2, 3 The inherent correlation among observations from the same cluster typically inflates type I error rates. Not accounting for non-independence within clusters can lead to incorrect estimation of the variance; p-values that are smaller than what a valid analysis will produce for intervention effects; and thus invalid inferences about intervention effects. 4 By valid analysis we mean an analysis which under the null hypothesis, with continuously distributed data and a continuously distributed test-statistic, produces a sampling distribution of p-values that is uniform on the interval [0, 1]. An invalid analysis refers to a testing procedure that produces any other sampling distribution of p-values.
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影响因子：
2.1
作者：
Sainani, Kristin
通讯作者：
Sainani, Kristin
影响因子：
2
作者：
Li, Peng;Redden, David T.
通讯作者：
Redden, David T.
影响因子：
15.1
作者：
Wang, Lei;Fang, Hong;Xu, Wanghong
通讯作者：
Xu, Wanghong
影响因子：
5.6
作者：
Murray, DM
通讯作者：
Murray, DM
影响因子：
6.1
作者：
Golzarri-Arroyo L;Dickinson SL;Jamshidi-Naeini Y;Zoh RS;Brown AW;Owora AH;Li P;Oakes JM;Allison DB
通讯作者：
Allison DB