Methods for modelling repeated measures in a lifecourse framework

医生们对健康的长期影响越来越感兴趣。例如，人们认为，婴儿出生时很小，童年时期成长得更快的人，在以后的生活中可能更有可能患上心血管疾病。纵向研究？对个体进行长达数月或数年的跟踪研究？对于理解人的方方面面是非常重要的吗？S童年的生活方式或环境如何影响他们后来的健康和福祉。当对同一个体进行多次测量(例如体重)时，不同年龄的值很可能是相关的。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(它们不同于如果分析是适当的就会观察到的结果)，或者导致不适当的结论(分析的结果被错误地解释)。已经提出了解决这些问题的统计方法，并有可能在纵向研究的分析中减少偏见并增加解释的简便性。然而，这些方法可能非常复杂，很难应用。我们将为应用这些方法的一些问题制定解决方案，包括制定随时间变化的模型(例如儿童成长)的战略，并将这种随时间变化与后来的结果联系起来。我们将把我们的新方法整合到现有的软件中，以最大限度地利用它们，并在科学期刊上发表结果。

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.