Repeated Measures Correlation.
Repeated Measures Correlation.
复制标题
DOI：
10.3389/fpsyg.2017.00456
复制
发表时间：
2017
影响因子：
3.8
通讯作者：
Marusich LR
中科院分区：
文献类型：
--
作者：
Bakdash JZ;Marusich LR
重复测量相关性（repeated measures correlation，rmcorr）是一种统计技术，用于确定多个个体在两个或两个以上场合评估的配对测量的共同个体内关联。简单的回归/相关通常应用于非独立的观察或汇总数据;由于违反独立性和/或参与者之间与参与者内部的不同模式，这可能会产生有偏见的，似是而非的结果。与简单回归/相关不同，rmcorr不违反观测独立性的假设。此外，rmcorr往往有更大的统计能力，因为平均或聚合是必要的，为一个内部的个人研究问题。Rmcorr估计了共同的回归斜率，即个体之间共享的关联。为了使rmcorr可访问，我们提供了背景信息，其假设和方程，可视化，电源，和权衡与rmcorr相比，多层次建模。我们介绍了R包（rmcorr），并展示了它的使用与两个示例数据集的推理统计和可视化。这些例子被用来说明研究问题在不同层次的分析，个人内部和个人之间。Rmcorr非常适合研究关于配对重复测量数据中常见线性关联的问题。所有结果均具有完全重现性。
Repeated measures correlation (rmcorr) is a statistical technique for determining the common within-individual association for paired measures assessed on two or more occasions for multiple individuals. Simple regression/correlation is often applied to non-independent observations or aggregated data; this may produce biased, specious results due to violation of independence and/or differing patterns between-participants versus within-participants. Unlike simple regression/correlation, rmcorr does not violate the assumption of independence of observations. Also, rmcorr tends to have much greater statistical power because neither averaging nor aggregation is necessary for an intra-individual research question. Rmcorr estimates the common regression slope, the association shared among individuals. To make rmcorr accessible, we provide background information for its assumptions and equations, visualization, power, and tradeoffs with rmcorr compared to multilevel modeling. We introduce the R package (rmcorr) and demonstrate its use for inferential statistics and visualization with two example datasets. The examples are used to illustrate research questions at different levels of analysis, intra-individual, and inter-individual. Rmcorr is well-suited for research questions regarding the common linear association in paired repeated measures data. All results are fully reproducible.