Key points are not available for this paper at this time.
Common hypotheses in psychiatric research regard relationships between latent variables such as risk-taking and ambiguity attitudes, alongside psychiatric symptoms. The prevailing methodological approach is to estimate the latent variables in a first step, and in a second step, use these estimates in the statistical analysis. Using estimates instead of their true values can lead to bias and reduced power. This study aims to develop a new hierarchical method, based on a Laplace-based variational approximation, to mitigate these issues. The developed method outperforms the prevailing method in terms of power, accuracy and out-of-sample prediction. An empirical example demonstrates the usefulness of the method. The developed approach is computationally efficient and suitable to apply to many data types.
Vegelius et al. (Fri,) studied this question.