We demonstrate how a linear factor model with latent variables can be used to estimate correlations between the outcomes of clinical trials. These correlations are needed for many policy questions of drug/vaccine development (such as calculating the optimal size of financial incentives) and the literature so far has relied on expert opinions. We apply our methodology to the case of vaccines and show that the estimated correlations are highly significant. We also illustrate how the estimated correlations can be used to find the probability of obtaining a successful vaccine out of a certain number of candidates and to determine optimal investment in vaccine development.

我们演示了如何使用具有潜在变量的线性因子模型来估计临床试验结果之间的相关性。药物/疫苗开发的许多政策问题（例如计算财务激励的最佳规模）都需要这些相关性，并且迄今为止的文献都依赖于专家的意见。我们将我们的方法应用于疫苗的案例，并表明估计的相关性非常显着。我们还说明了如何使用估计的相关性来找出从一定数量的候选疫苗中获得成功疫苗的概率，并确定疫苗开发的最佳投资。