Aim We aimed to identify measures used to assess the participation of disabled children and
to map the measures' content to the family of participation‐related constructs (fPRC) to …

Childhood trauma (CT) has been identified as a potential risk factor for the onset of psychotic
disorders. However, to date, there is limited consensus with respect to which symptoms may …

We consider constraint-based methods for causal structure learning, such as the PC-, FCI-,
RFCI-and CCD-algorithms (Spirtes et al., 1993, 2000; Richardson, 1996; Colombo et al …

The pcalg package for R can be used for the following two purposes: Causal structure
learning and estimation of causal effects from observational data. In this document, we give …

Autism spectrum disorder is associated with diverse social, educational, and occupational
challenges. To date, no standardized, internationally accepted tools exist to assess autism …

Modern psychiatric epidemiology researches complex interactions between multiple
variables in large datasets. This creates difficulties for causal inference. We argue for the …

Discovering the causal mechanisms of biological systems is necessary to design new drugs
and therapies. Computational Causal Discovery (CD) is a field that offers the potential to …

Background We develop predictive models enabling clinicians to better understand and
explore patient clinical data along with risk factors for pressure ulcers in intensive care unit …

Musical abilities and active engagement with music have been shown to be positively
associated with many cognitive abilities as well as social skills and academic performance …

Random Forests in combination with Stability Selection allow to estimate stable conditional
independence graphs with an error control mechanism for false positive selection. This …