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Qual Life Res. 2022 Dec;31(12):3433-3445. doi: 10.1007/s11136-022-03198-9. Epub 2022 Aug 5.
Quality of life research often collects daily information and averages this over a week, producing a summary score. When data are missing, arbitrary rules (such as requiring at least 4/7 observations) are used to determine whether a patient's summary score is created or set to missing. This simulation work aimed to assess the impact of missing data on the estimates produced by summary scores, the psychometric properties of the resulting summary score estimates and the impact on interpretation thresholds.
Complete longitudinal data were simulated for 1000 samples of 400 patients with different day-to-day variability. Data were deleted from these samples in line with missingness mechanisms to create scenarios with up to six days of missing data. Summary scores were created for complete and missing data scenarios. Summary score estimates, psychometric properties and meaningful change estimates were assessed for missing data scenarios compared to complete data.
In most cases, the 4/7 day rule was supported, but this depended on daily variability. Fewer days of data were sometimes acceptable, but this was also dependent on the proportion of patients with missing data. Tables and figures allow researchers to assess the potential impact of missing data in their own studies.
This work suggests that the missing data rule used to create summary scores impacts on the estimate, measurement properties and interpretation thresholds. Although a general rule of 4/7 days is supported, the way the summary score is derived does not have a uniform impact across psychometric analyses. Recommendations are to use the 4/7 rule, but plan for sensitivity analyses with other missing data rules.
生活质量研究通常会收集每日信息，并将其平均分布在一周内，得出一个总结分数。当数据缺失时，会使用任意规则（例如要求至少有 4/7 的观察值）来确定患者的总结分数是否创建或设置为缺失。本模拟研究旨在评估缺失数据对总结分数产生的估计值的影响、由此产生的总结分数估计值的心理测量特性以及对解释阈值的影响。
为具有不同日常可变性的 400 名患者的 1000 个样本模拟完整的纵向数据。根据缺失机制从这些样本中删除数据，以创建多达六天缺失数据的场景。为完整数据和缺失数据场景创建总结分数。评估缺失数据场景中总结分数估计值、心理测量特性和有意义变化估计值与完整数据的比较。
在大多数情况下，支持 4/7 天规则，但这取决于日常可变性。有时可以接受更少的天数数据，但这也取决于缺失数据患者的比例。表格和图形允许研究人员评估缺失数据在其研究中的潜在影响。
这项工作表明，用于创建总结分数的缺失数据规则会影响估计值、测量特性和解释阈值。虽然支持 4/7 天的一般规则，但总结分数的推导方式不会对心理测量分析产生统一的影响。建议使用 4/7 规则，但要计划使用其他缺失数据规则进行敏感性分析。
