METHODS: Logistic regression models were fitted to compute the probability of (i) Responding given envisioned to take part, (ii) Responding timely given responded, and (iii) (Re)infection given timely response. Response, timely response and (re)infection weights were generated as the reciprocal of the corresponding probability, with an overall \'envisioned population\' survey weight derived as the product of these weights. Survey weights were trimmed, and an interactive tool developed to re-calibrate target population survey weights to the general population using data from the 2021 UK Census.
RESULTS: Flexible survey weights for the CLoCk study were successfully developed. In the illustrative example, re-weighted results (when accounting for selection in response, attrition, and (re)infection) were consistent with published findings.
CONCLUSIONS: Flexible survey weights to address potential bias and selection issues were created for and used in the CLoCk study. Previously reported prospective findings from CLoCk are generalisable to the wider population of CYP in England. This study highlights the importance of considering selection into a sample and attrition over time when considering generalisability of findings.
方法:对Logistic回归模型进行拟合,以计算(i)预期参与的响应的概率,(二)给予及时回应,和(iii)(Re)感染给予及时反应。回应,及时响应和(再)感染权重被生成为相应概率的倒数,总体的“预期人口”调查体重是这些体重的乘积。调查重量被修剪,以及开发的交互式工具,使用2021年英国人口普查的数据将目标人口调查权重重新校准为一般人口。
结果:成功开发了用于CLoCk研究的灵活调查权重。在说明性示例中,重新加权的结果(当考虑响应选择时,自然减员,和(再)感染)与已发表的发现一致。
结论:为CDoCk研究创建并使用了灵活的调查权重,以解决潜在的偏见和选择问题。先前报道的来自CLoCk的前瞻性发现可推广到英格兰的CYP更广泛的人群。这项研究强调了在考虑发现的普遍性时,考虑选择样本和随时间流失的重要性。