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.
Keywords: 62P10; 62P20; 62Pxx; Applications of statistics; clinical trials; correlations; factor models; latent variables; maximum likelihood.
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