Methods for modelling repeated measures in a lifecourse framework

医生们越来越关注对健康的长期影响。例如，人们认为，婴儿出生时身材矮小，儿童时期生长较快的人，在以后的生活中更有可能患心血管疾病。纵向研究？研究中对个体进行了数月或数年的跟踪？对了解人类的各个方面都很重要儿童的生活方式或环境影响他们以后的健康和幸福。当一个测量（例如体重）在同一个人身上进行多次测量时，不同年龄的值可能是相关的。这在纵向研究的数据分析中提出了困难的问题，如果不能适当地解决这些问题，可能会导致有偏见的结果（它们与分析适当时观察到的结果不同）或导致不适当的结论（分析结果被错误地解释）。已经提出了解决这些问题的统计方法，并有可能减少偏倚，增加纵向研究分析的解释。然而，这些方法可能非常复杂并且难以应用。我们将制定一些问题的解决方案，应用这些方法，包括制定战略，随着时间的推移（例如，在童年的增长）建模变化，并随着时间的推移，这种变化与以后的结果。我们将把我们的新方法整合到现有的软件中，以最大限度地提高其未来的使用价值，并将结果发表在科学期刊上。

Doctors are increasingly interested in long-term influences on health. For example, it is thought that people who were born small as babies, and grew faster during childhood, may be more likely to suffer cardiovascular disease in later life. Longitudinal studies ? studies in which individuals are followed over periods of many months or years ? are of great importance in understanding how aspects of people?s childhood lifestyle or environment influence their later health and wellbeing. When one measure (e.g. weight) is made several times on the same individual, the values at different ages are likely to be related. This raises difficult issues in the analysis of data from longitudinal studies, and failing to address these appropriately can lead to results that are biased (they differ from the results that would be observed if the analysis had been appropriate) or lead to inappropriate conclusions (the results of the analyses are interpreted incorrectly). Statistical methods that do address these issues have been proposed, and have the potential to decrease bias and increase ease of interpretation in analyses of longitudinal studies. However, these methods can be highly complex and difficult to apply. We will develop solutions to some of the problems with applying these methods, including developing strategies for modelling change over time (e.g. growth in childhood), and relating this change over time to later outcomes. We will incorporate our new methods into existing software, to maximise their future use, as well as publishing the results in scientific journals.