A frequent problem in longitudinal studies is that data may be assessed at subject‐selected, irregularly spaced time‐points, resulting in highly unbalanced outcome data, inducing bias, especially if availability of data is directly related to outcome. Our aim was to develop a multivariate joint model in a mixed outcomes framework to minimize irregular sampling bias. We demonstrate using blood glucose monitoring throughout pregnancy and risk of preterm birth among women with type 1 diabetes mellitus. Blood glucose measurements were unequally spaced and intensity of sampling varied between and within individuals over time. Multivariate linear mixed effects submodel for the longitudinal outcome (blood glucose), Poisson model for the intensity of glucose sampling, and logistic regression model for binary process (preterm birth) were specified. Association between models is captured through shared random effects. Markov chain Monte Carlo methods were used to fit the model. The multivariate joint model provided better prediction, compared with a joint model with a multivariate linear mixed effects submodel (ignoring intensity of glucose sampling) and a two‐stage model. Most association parameters were significant in the preterm birth outcome model, signifying improvement of predictive ability of the binary endpoint by sharing random effects between glucose monitoring and preterm birth. A simulation study is presented to illustrate the effectiveness of the multivariate joint modeling approach.

中文翻译：

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用于频繁收集数据的医学监测的纵向强度和二进制过程的灵活多变量联合模型

纵向研究中的一个常见问题是，数据可能在受试者选择的、不规则间隔的时间点进行评估，导致结果数据高度不平衡，导致偏倚，尤其是在数据的可用性与结果直接相关的情况下。我们的目标是在混合结果框架中开发一个多元联合模型，以最大限度地减少不规则抽样偏差。我们展示了在 1 型糖尿病女性中使用整个怀孕期间的血糖监测和早产风险。血糖测量的间隔不均，采样强度在个体之间和个体内部随时间变化。指定了纵向结果（血糖）的多元线性混合效应子模型、葡萄糖采样强度的泊松模型和二元过程（早产）的逻辑回归模型。模型之间的关联是通过共享随机效应捕获的。马尔可夫链蒙特卡罗方法用于拟合模型。与具有多元线性混合效应子模型（忽略葡萄糖采样强度）和两阶段模型的联合模型相比，多元联合模型提供了更好的预测。大多数关联参数在早产结果模型中是显着的，这表明通过共享葡萄糖监测和早产之间的随机效应来提高二元终点的预测能力。提出了一项模拟研究来说明多变量联合建模方法的有效性。与具有多元线性混合效应子模型（忽略葡萄糖采样强度）和两阶段模型的联合模型进行比较。大多数关联参数在早产结果模型中是显着的，这表明通过共享葡萄糖监测和早产之间的随机效应来提高二元终点的预测能力。提出了一项模拟研究来说明多变量联合建模方法的有效性。与具有多元线性混合效应子模型（忽略葡萄糖采样强度）和两阶段模型的联合模型进行比较。大多数关联参数在早产结果模型中是显着的，这表明通过共享葡萄糖监测和早产之间的随机效应来提高二元终点的预测能力。提出了一项模拟研究来说明多变量联合建模方法的有效性。